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  • US$75 hourly
    Hi! I am a Data Scientist (M.S. Operations Research) with 9+ years of experience developing data-centric solutions that create business value. From python to excel, user facing web applications to backend data collection and cleaning, I have experience across the data science spectrum: • Data Collection (API, Web Scraping, Document Parsing) • Data Manipulation (JSON, HTML, XML, Excel, CSV) • Data Visualization (Static and Interactive) • Modeling (Inference and Prediction) • Automation • Dashboard Design (Shiny, Excel) I have previously developed solutions using Python, R, SQL, VBA, Excel, and Linux. Most of all, I am passionate about using data to solve problems and improve processes.
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    Quantitative Analysis
    Data Analysis
    R Shiny
    Data Scraping
    Spreadsheet Software
    Machine Learning
    ETL
    Data Science
    Linear Regression
    Data Visualization
    Dashboard
    SQL
    Python
    Microsoft Excel
  • US$78 hourly
    I am an experienced data scientist who has worked in Bioinformatics and Business analytics. I build automated trading strategies in my spare time. I've been programming in R daily for over 10 years and that's where I do most of my data analysis. I have a lot of experience with machine learning and data visualizations, mainly in R and Shiny. Working in a diverse set of fields has given me experience with many different types of data and obtaining it from many different sources. Thereby making me an excellent data miner, and knowing how to transform that data efficiently.
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    Data Analysis
    R Shiny
    API
    Forex Trading
    Statistics
    Analytics
    Bioinformatics
    Quantitative Analysis
    Data Scraping
    Plotly
    Machine Learning
    Data Visualization
    Data Science
  • US$50 hourly
    I am a freelance data analyst, research/statistics adjunct professor, and educational psychology Ph.D. student with a strong foundation in statistics and data analysis. I have 6+ years of experience in research/data analytics, social and behavioral science research, and teaching college students (both at the undergraduate and graduate level). I am fluent in numerous statistical analysis programs such as SPSS, R/Rstudio, and JASP. I enjoy conducting quantitative analysis and problem-solving. Please feel to contact me with all your research and data analysis inquiries. Educational and Research Background: I am currently an educational psychology Ph.D. Student. I have both my master's degree and a bachelor's degree in psychology. I have conducted numerous research projects revolving around the identity formation of emerging adults' college students. I have a year's worth of experience as a research analyst intern where I conducted data analysis for numerous population health-based projects which topics included: resident burnout, dystocia, ventilation survivability, clinician bullying preparedness, the hospital-based prevalence for medical cases (i.e. domestic violence, lead poisoning, immunization records, and child abuse) and medical cases NYC GIS mapping (i.e. lead poison, eating disorders, domestic violence, etc.). My master thesis examined the differences in vocational identity and coping strategies among emerging adults in college by their current employment status and work experiences. Main Services Includes (but not limited): Statistical Analysis Creating Data Visualization Graphs & Tables for Statistical Results Writing APA-Style Statistical Reports Writing General Summary for Statistical Results Creating PowerPoint Presentations for Statistical Results Statistical Programs/Software Skills: SPSS R/RStudio JASP Jamovi GPower Excel Statistical Analysis Skills Include: Descriptive Statistics Data Visualization Linear Regression Models Generalized Linear Models (i.e., logistic, poison, ordinal. etc.) Moderation and Mediation Analysis t-test ANOVA Models (ANOVA/ANCOVA/MANOVA) Linear Discriminant Analysis Hierarchical/Multilevel Regression Models Factor Analysis (Exploratory and Confirmatory) Path Analysis and Structural Equation Modeling Non-Parametric Analysis Power Analysis Robust Statistics Supervised Machine Learning Algorithms (Linear Regression, Logistic Regression, Decision Trees, etc.) Unsupervised Machine Learning Algorithms (Kmeans, K nearest Neighbors, Apiori etc.) Other Skills: Advanced in Microsoft Office Programs (i.e. Word, Excel, PowerPoint) Proficient with Python Programming language Proficient with online survey distribution programs such as Qualtrics, Survey Monkey, Google Survey, and REDCap Proficient with digital movie maker programs such as Windows Movie Maker and I-Movie
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    Data Analysis
    Statistical Analysis
    Statistics
    Tutoring
    Quantitative Analysis
    Hypothesis Testing
    Logistic Regression
    Data Visualization
    Machine Learning
    IBM SPSS
    Linear Regression
  • US$300 hourly
    I am an evangelist of the power of data to support decision-making for business. I also have a special interest in supply chain (which was the focus of my PhD). I use any and all tools necessary in order to understand a project and solve it effectively. I ensure I am working on the right problem and then use my technical expertise to deliver for my clients. I have spent 5 years working as a data consultant in a range of application domains. I am SnowPro Core certified, an INFORMS Certified Analytics Professional, and have my AWS Certified Data Analytics Specialty. Part of the Upwork Expert Vetted program (top 1% of the marketplace)
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    Operations Research
    Linear Programming
    Forecasting
    Mathematics
    Business Intelligence
    Algorithm Development
    Time Series Forecasting
    Quantitative Analysis
    Supply Chain Management
    Inventory Management
    Linear Regression
    Snowflake
    Data Science
    Data Analysis
    Python
    SQL
  • US$75 hourly
    An experienced, independent, and commercially minded scientist with a documented history of working in neuroscience. Results-oriented with strong technical and commercial abilities. Strong analytical skills, including data visualization, interpretation, scientific writing, and presentation development/delivery. Skilled in delivering passionate scientific communications and presentations to peers and non-experts. Fond of teaching basic biology to students beginning their academic careers.
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    Publication Design
    Grant Writing Consultation
    Biology Consultation
    Science
    Scientific Illustration
    Science & Medicine
    Resume Design
    Resume Development
    Resume Writing
    Manuscript
    Data Analytics & Visualization Software
    Editing & Proofreading
    Scientific Writing
    Scientific Computation
  • US$50 hourly
    "Vignesh's understanding of end client business requirements and converting that to deliverable is quite strong." "Very well done job! Vignesh proved to have excellent skills and an ability to find solutions" "Vignesh went beyond my expectations in everything he did with regard to Tableau and BigQuery Integration." Overall Experience - 6+ Years Expertise in Tableau and experience in Data Visualization tools, including PowerBI, Qlikview, Google Data Studio, Slemma - 6+ Years experience in Data Processing using SQL, R, Python, PySpark, BigQuery, Redshift ETL Tools (Alteryx, Dataiku) - Top Rated Freelancer in Upwork for 4+ years - Have worked for 20000+ hours, 80+ clients
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    Amazon Redshift
    Snowflake
    Data Analysis
    BigQuery
    Alteryx, Inc.
    Exploratory Data Analysis
    Data Science
    Data Modeling
    SQL Programming
    Data Visualization
    Python
    Looker Studio
    SQL
    Tableau
  • US$55 hourly
    As an R Shiny developer, I specialize in creating user-friendly data visualization apps. With experience in crafting dashboards and interactive interfaces, I enjoy making complex data accessible. My goal is to deliver practical solutions that align with clients' needs. Let's work together to turn your data into a clear and engaging story using R Shiny.
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    Visual Basic for Applications
    PostgreSQL Programming
    Data Analysis
    Data Mining
    R Shiny
    Data Science
    Data Visualization
    SAS
    ggplot2
    Microsoft Excel
    SQL
  • US$145 hourly
    I offer excellent data analysis and visualization using R or Python. Furthermore, i will conduct your Machine-Learning project. That can include data cleaning, manipulation, feature engineering, evaluation and deployment of machine-learning-models (also Deep Learning), and explaining of black box models. Need help with statistics in your studies? I provide you with well-explained input. Need help with your R-code? I will debug your script and/or give a code review. ✔️ more than 60.000 lines of R-code experience ✔️ R-package development, R-shiny, and R-markdown experience ✔️ SQL and Python coding ✔️ Theoretical and practical understanding of machine learning algorithmics ✔️ Master of Science Statistics with focus on Data Science ✔️ Finished 9th in Data Mining Cup 2017 out of 202 Teams Feel free to contact me anytime, I am curious to hear about your challenges. I am looking forward to working with you!
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    Code Review
    Data Analysis
    PostgreSQL
    Software Debugging
    ggplot2
    Time Series Analysis
    Data Science
    Machine Learning
    XGBoost
    Random Forest
    Python
    Convolutional Neural Network
    Artificial Neural Network
  • US$25 hourly
    I am an experienced Ecological Modeller and R Programmer, with a passion for creating data-driven insights for conservation and biodiversity. My expertise in Spatial Ecology and Ecological Niche Modelling allows me to effectively model and analyze complex ecological systems using R programming. Over the past two and a half years, I have developed a strong understanding of spatial analyses and modelling in R, and have become well-versed in acquiring, cleaning, and georeferencing both species and climatic data. I have worked with multiple models, including eight different algorithms of three families: Tree-based, Regression-based, and Machine-Learning. I am also proficient in most spatial related R packages (raster, sp, terra, sf, tmap, leaflet, rayshader) syntax and the back and forth between them. In my recent work, I have extended my expertise beyond Ecological Niche Modelling to a wide range of quantitative modelling approaches, including quantitative population genetics, epidemiology, and network ecology. I have experience using various approaches such as game theory, differential, and markov processes. I have a strong research background in Macroecology, Biogeography, Evolution, and Ecological Niche Modelling. My work has led me to take an interest in computational and spatial ecology. Modelling ecological systems is what delights me, and I am fascinated by what can be achieved through math and code alone, and how much we can explore of the natural world through this lens. In addition to my research experience, I have also developed my own R package, sdmLit, which allows users to apply tools that analyze model performance, check environmental consistency, and build ensemble models by frequency to Ecological Niche Models. This package automates the data manipulation process and makes it easier to use literature methods, which previously required several thousand lines of code. My dedication to ecological modelling and R programming has helped me to become a skilled and detail-oriented professional. I am always eager to learn and take on new challenges, such as implementing individual-based models in spatial settings. I am confident that my skills and expertise can bring value to any project related to ecological modelling, data analysis, and conservation. If you are looking for a dedicated and knowledgeable Ecological Modeller and R Programmer, please don't hesitate to get in touch.
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    Ecological Engineering
    Microsoft Excel
    Data Analytics
    Georeferencing
    Spatial Analysis
    Cartography
    Map Illustration
    GIS
    Data Visualization
    QGIS
    Data Analysis
    Statistics
    LaTeX
    Biology
  • US$55 hourly
    I am a data scientist who developed different end-to-end data solutions for the Internet Of Things. I have the tools to develop your IoT, time series or data science projects. I focus on providing clean and reusable code that becomes an asset to your solution. Skills ------ * Professional developer for data science in R, Python * Expertise in time series: forecasting, classification, anomaly detection * Methodology for data science project: from data preparation to experiment * Focus on your KPI * Clear communication, present technical results simply Work experience -------------------- I have four years of industry experience in data science. At the energy research institute in Singapore, during three years. I have developed analytics for a smart building management system that was installed on 30+ industrial and academic buildings. My work in forecasting accuracy and optimization had a significant impact on the operational costs. As a freelance for more than a year, I have developed for SunCulture a credit scoring algorithm for farmers. The algorithms implemented considerably reduce the risk of credit lending. Education ------------ I have a master in statistics and machine learning from Telecom SudParis a selective French engineering school. This master included rigorous mathematics, statistics and probabilities courses. A good background in statistics is needed to convert data to sensible interpretations and actions.
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    Digital Signal Processing
    Internet of Things
    SQL
    Time Series Analysis
    Python
    TensorFlow
    Deep Learning
    Statistics
    Machine Learning
  • US$40 hourly
    Data Analytics developer with 3+ years of experience leading data-driven solutions from data architecture, dashboards, and statistical analysis with professional experience working in a Fortune 500 company 🖊️ I have worked with clients ranging coming from ➡️ 1. E-Commerce 2. NGO 3. Academia 4. Tech 5. Pharma 🤝 My service when you hire me ➡️ Optimize your Data Workflow Architecture & Warehouse: ✔️ AWS: S3, Lambda, ECS, Glue, EMR, Redshift, DynamoDB ✔️ Programming: Python, R, SQL, Spark Develop Dashboard to Automate Reporting: ✔️ RShiny ✔️ Python Dash ✔️ AWS QuickSight ✔️ Google Data Studio Drive Insights through Statistical Analysis and Data Viz: ✔️ Python: Pandas, Matplotlib, Seaborn ✔️ R: Tidyverse, ggplot, ggpubr ✔️ Notebooks: Jupyter Notebooks, RMarkdown ✔️ A/B Testing, Time-Series Analysis, Multi-Regression ✔️ Supervised Machine Learning Let's connect and I will help you solve your problems!
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    AWS Glue
    Amazon Redshift
    Amazon Web Services
    AWS Lambda
    R Shiny
    Docker
    Git
    A/B Testing
    Python
    Tableau
    SQL
    Data Visualization
    Data Science
    Machine Learning
  • US$150 hourly
    I will work with you to analyze your needs/data and design complete data analytics solutions which provide you automated insights with full picture into your sales, marketing, operational efforts, etc. In addition, I have extensive experience with Domo bricks (Javascript, HTML & CSS). List of data sources I worked with: ✅ Amazon RDS ✅ Bing Ads ✅ Facebook (Meta) Ads ✅ Facebook Page Insights ✅ Google Ads ✅ Google Analytics ✅ Google BigQuery ✅ Hubspot ✅ Infusionsoft ✅ Instagram Ads ✅ Klaviyo ✅ LinkedIn Ads ✅ Maria DB ✅ Microsoft SQL Server ✅ MySQL ✅ QuickBooks ✅ RSS ✅ Salesforce ✅ Shopify ✅ SurveyMonkey The focus in my work is on creating both visually appealing and clear, user-friendly dashboards. With a Masters degree in Business and a diverse background in marketing, finance, operations, e-commerce and account management, I can relate to the majority of my clients and understand their true needs faster. Specifically, I can help you: Identify the strategic objectives for your business Define Key-Performance-Indicators (KPIs) and appropriate measures across different teams in your organization Custom analytical tools used on a daily, weekly or monthly basis for you, your employees or co-workers Complex and intricate financial models including forecasting, predictions, ROI calculators for product features and sales team for any stage of business Visualizing and managing large sets of complex data for executive reporting, data manipulation, and data analysis Complex formula development (some of my excel formulas take half a page or more) I discovered my true passion for analytics about 9 years ago while working for e-commerce business. Since then I dedicated myself to every opportunity to learn, evolve, and establish myself in this field. I fell in love with financial modeling, predictions, forecasting and other data science techniques later in my career. I’m eager to learn about your business and goals, but even more so to share the best way analytics can help you win. I can’t guarantee we’ll be a fit, but I can guarantee you won’t regret hearing how I can help. (You’ll probably get some free learnings too!)
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    LookML
    Data Extraction
    ETL Pipeline
    Looker Studio
    BigQuery
    Business Intelligence
    Microsoft Excel
    Domo
    SQL
    Data Analysis
    Looker
    Dashboard
    Google Sheets
    Data Visualization
  • US$60 hourly
    I am a statistician with more than 10 years of experience working as an independent consultant. My expertise areas are design of experiments, modeling and data analysis. I have experience with R, SAS, SPSS and Minitab. I have a degree and a PhD in Statistics from the National University of Rosario (UNR). In 2009 I received my BA in Statistics and in 2016 I finished my PhD in Statistics. My doctoral thesis addressed issues of design of experiments and was carried out under the mentorship of Prof. Christopher J. Nachtsheim of the University of Minnesota, USA. Since 2011, I provide consultancy and teach courses in companies and industries on specific topics in the area such as design of experiments and statistical process control. Likewise, provide biostatistical consulting to different institutions and professionals who work in areas related to health and clinical research. Between October 2019 and November 2021, I was part of the IQVIA Biostatistics department. Between April 2010 and March 2021, I worked as a professor at the Faculty of Economic Sciences and Statistics of the National University of Rosario (Argentina) in the subjects Design of Experiments, Sampling Methods in Censuses and Surveys, Data Collection and Primary Treatment of Information, among others. I have also taught postgraduate courses in various master's and doctoral programs.
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    Experiment Design
    Statistical Process Control
    Biostatistics
    Modeling
    Survey Design
    Linear Regression
    Exploratory Data Analysis
    Survey Data Analysis
    Statistical Analysis
    Statistics
    Hypothesis Testing
    Minitab
    Data Analysis
    SAS
  • US$60 hourly
    I’m a Certified Data Analytics and Business Intelligence Specialist, with a background in economics, management, econometrics and a Master degree in Marketing Management. I have been helping businesses, from startups to large public corporations, to gain insights from their data and make better decisions for more than 14 years. I am passionate about Data and my client's challenges. I enjoy pushing the envelope, answering hard business questions, solving difficult problems, optimizing business processes, writing clean and efficient pipelines and informative Data Visualizations. My certifications: - Microsoft Certified: Data Analyst Associate (H859-1477) ; - Microsoft Certified: Power Platform Fundamentals (H680-4568) ; - Google Analytics Individual Certification (ID: 43650393) ; - Google Tag Manager Fundamentals ; - SAS Customer Intelligence 360 certification I am experienced in the following fields and technologies: - Business Intelligence and Analytics: R, Python, Pentaho, DAX, T-SQL, MS-Excel - Data Mining and Integration: SAS Data Mining, Pentaho Kettle, Knime, SSIS, Apache Airflow, ETL on Python, Azure Functions for ETL, Power Automate, Data extraction via API, Setting up API using Flask and Plumber - Data Warehouse and Database development: Azure SQL Data Warehouse, SQL Server, Postgresql, MySql - E-commerce and Web Analytics: Google Analytics and API, Google Tag Manager, Google Ads and API, Facebook Analytics and API, Acoustic, SAS Customer Intelligence 360, SEO Marketing, Web scraping, Data Mining of Social Media, Market Research, Advanced Metrics dashboard - Big Data: Hadoop, Hive, Spark, BigQuery, Databricks - Data Visualization and Applications: Power BI, Google Data Studio, Tableau, R Shiny Apps, Plotly Dash, Dynamic Rmarkdown notebooks, Apache Superset, Power Bi custom Visuals, Power Bi custom connectors - Machine learning and Time Series Forecast: Advanced Linear Model, Random Forest algorithm, Scilik-Learn, Keras, Tidymodel & Caret, Parallel training using azure clusters, I also lead a well-trained team of data analysts and data scientists, ready to be allocated if needed. All members go under a strict selective process and confidentiality contract.
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    Data Modeling
    Microsoft Azure
    Analytics
    Machine Learning
    Data Science
    SQL
    Google Analytics
    Python
    BigQuery
    Business Intelligence
    Data Analysis Expressions
    Marketing Analytics
    Microsoft Power BI
    Data Analysis
  • US$25 hourly
    I am a statistician and expert R programmer with more than 10 years of professional experiences. I wish to be an expert in statistical fields and seek to help individuals, groups, or companies solving their statistical problems in various type of disciplines. My expertise includes survey data analysis (U&A, NPS, SEM, key driver analysis, segmentation, factor analysis, etc.), data mining, dissertation assistance, report writing, and database management. I am proficient in R, SPSS, Excel, and VBA programming. I have my Master's degree in Biostatistics and also have experiences in healthcare data or medical research study.
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    Biostatistics
    Data Analysis
    Data Visualization
    Statistics
    Microsoft Excel
  • US$75 hourly
    ⭐⭐⭐ Expert-Vetted, top-1% talent on Upwork ⭐⭐⭐ Are you struggling to develop or optimize your R Shiny applications? If yes, then you are at the right place. As an experienced R Shiny developer and bioinformatician, I can help you develop, audit, or optimize your R/Shiny applications. With my expertise in UI/UX development and data science, I can provide custom solutions that are both functional and visually appealing. WHY ME ----- ✅ Over 12 years of programming experience in R and 8+ years of experience developing Shiny applications ✅ PhD in Plant Biology from UT Austin and over 6 years of postdoctoral research experience. ✅ Advanced and rapid developer of Shiny applications, with a flexible and adaptable approach that allows me to handle steep learning curves with reasonable time frames. ✅ My background in biology and bioinformatics, and the domain-specific knowledge necessary to develop software solutions will help to meet your specific business needs. WHAT I OFFER ----- ✅ R Shiny application development, audit, or optimization (base Shiny, Golem, or Rhino) ✅ R package development, audit, or optimization ✅ Plumber API development ✅ Bioinformatics pipeline development (Docker-based systems for deployment to AWS or GCP) ⭐ I am committed to going above and beyond for my clients and always strive to deliver high-quality projects on time and within budget. Have questions? I’m just a message away from you! 🤝
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    Statistical Analysis
    SQL
    Machine Learning
    Git
    Microsoft Excel
    Big Data
    Data Mining
    R Shiny
    Data Science
    Docker
    Data Visualization
    Data Analysis
    Dashboard
    Bioinformatics
  • US$210 hourly
    Expert Vetted & Top Rated Plus Freelancer! Summary of Skills: Looking to provide data driven insights to companies and people using applied mathematics, statistics, and human ingenuity. My primary language is R, but also use Excel extensively and for business compatibility. Also, have SQL experience. Previously worked for a Fortune 500 tech company (Symantec in internet security) doing business statistics and data analysis. Graduate of Claremont Graduate School with a Masters in Mathematics in 2013. Graduated from Santa Clara University in Finance and Mathematics with an emphasis in applied math and minor in physics. Looking to help people and companies gather and interpret data using mathematical and statistical techniques. Brief Background: In recent years, I have been providing consulting in a variety of analytic fields including technology, healthcare, gaming, financial, legal (patents and data research for court cases), and others. I make sense of your data so you can spend more time making informed decisions or asking deeper level questions. Since college I have tutored a wide variety of people in math from middle school to the MBA level. I have covered subjects including, calculus, statistics, and multi-variable regression modeling. At Santa Clara I worked in the Drahmann Center as a tutor to help my fellow students with their classwork and learning, specifically in math.
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    Statistical Analysis
    Marketing Analytics
    Microsoft Excel
    Price Optimization
    Data Science
    Analytics
    Data Interpretation
    Business Mathematics
    Data Modeling
    Data Visualization
    Statistics
    Algorithm Development
    Tutoring
    Mathematics
  • US$70 hourly
    I am a data scientist with academic training in epidemiology and 5+ years of working experience in data analytics for both government organizations and consulting firm. I have experience on those projects: - Developing data visualization products using R Shiny, Microsoft PowerBI or Tableau - Conducting observational studies using insurance claim data, health administrative data such as HCUP NIS, NEDS , Truven MarketScan and etc. - Building prescriptive or predictive models (mixed effect model, logistic regression, clustering, decision tree, etc.) - Web scraping for data acquisition - Reports automation I excel at listening to clients' needs and delivering projects on time and within budget.
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    Data Modeling
    Public Health
    Forecasting
    Epidemiology
    R Shiny
    Machine Learning
    Logistic Regression
    Linear Regression
    Data Science
    Microsoft Power BI Data Visualization
    Data Visualization
    Data Analysis
    Python
    SQL
  • US$75 hourly
    You need to write a paper? The deadline is soon? There is statistics involved, and you just don't like that stuff? You don't have time or the nerves to do it? You wrote it but now it doesn't look like it should? And what's with the pesky rules about referencing? I'm here to help. With 6 years of experience in academic writing and a Master's degree in research psychology, I can make your paper shine! What you can expect from me: Detailed, error-free papers - either edited or written from scratch Correct referencing and formatting (APA, MLA, etc.) Professional style and great flow Statistical analyses conducted via SPSS, STATA, Jamovi, or R (t-test, chi square, regression, ANOVA, EFA, CFA and anything else you might need) Respect for deadlines Great, constant communication So look no further! Send me that job and let's see what we can do about it.
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    Writing
    Statistics
    Stata
    Academic Writing
    Fact-Checking
    APA Formatting
    Data Analysis
    Scientific Writing
    Qualitative Research
    Quantitative Research
    Microsoft Excel
    Academic Proofreading
    Academic Editing
    Survey Design
  • US$60 hourly
    1. Advanced R Shiny Apps 2. Javascript, CSS & HTML, integrating with R shiny apps 3. R Markdown/ flexdashboard reports, automation 4. R Packages 5. HTMLWidgets with R 6. Website/ blog with R ** No Assignments/ tests/ homework please, owing to Ethical Issues. I enjoy working with the aforementioned topics, but my domain isn't confined to them only. Basically, anything related to R programming and I am up for it! A statistician turned developer and an R lover, that would be me! By the dint of Allah the Almighty, I have been coding in R for ~5 years now and have learnt some tricks, still a long way to go though! Ever since my introduction to R, Shiny & the wonderful community, I never looked back. I may have worked with Python for about a year, but I call myself a full time R developer now. Being a Statistician, I used to analyse data, find hidden insights and present it to the mass people using reports and workbooks. Now I do almost the same thing, only with Dashboards and Web Applications, and of course, with R! Alhamdulillah, I have a website which is focused mainly on R. If one has the time, I'd say please pay a visit. (The link should be somewhere in the profile, I'm not sure where!) A tiny achievement, An Honorary Mention in the Shiny-Contest-2020, hosted by RStudio, for an app titled 'Life of Pi'. One may find it in the portfolios section. That's pretty much it. Do connect if you feel like it. Zauad
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    CSS
    RStudio
    Biostatistics
    Data Science
    R Shiny
    Data Analysis
    ggplot2
    JavaScript
    Dashboard
    Data Visualization
  • US$50 hourly
    I am an experienced developer with building scalable data driven systems for wide variety of industries. My expertise is python, flask, flutter, Angular
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    Amazon Web Services
    Data Structures
    Flask
    Docker
    AWS Lambda
    Serverless Computing
    Kubernetes
    AWS CloudFront
    R Shiny
    Python
  • US$60 hourly
    I'm a quantitative analyst and statistical programmer with a PhD in mathematics from the University of Wisconsin-Madison. I have experience with Python and R, as well as a working knowledge of SQL. I have a particular interest in social research and policy (for example housing, demography, poverty, education, health), so if you have such a project I'd love to hear from you.
    vsuc_fltilesrefresh_TrophyIcon R
    Statistical Programming
    Data Analysis
    Data Extraction
    GNU Octave
    Python
    Machine Learning
    Quantitative Analysis
    SQL
    Data Scraping
    MATLAB
    Statistics
  • US$138 hourly
    Cornell/MIT educated data scientist with financial modeling and digital analytics experience at Fortune 500 companies. • Academic experience as TA/RA at MIT and Cornell University. • Advanced R, Python, SPSS, SAS, Tableau, SQL, MPlus. Some of the projects I have done are: • Time series analysis, financial forecasting and other econometric methods • ANOVA, MANOVA, GLM, SEM in social sciences • Biostatistics and medical research including analysis of clinical trials • Regression modeling • Machine learning and various statistical models in big data • Valuation, investment analysis and financial modeling in the investment banking industry • Risk modeling • Computer vision • Digital analytics such as campaign analysis for display (Facebook Ads, Google Ad Manager, etc.), customer insights (Facebook Insights), lead tracking (CallRail), SEM/PPC (Google Ads), and web traffic (Google Analytics) analysis
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    Regression Testing
    Statistics
    Product Analytics
    Google Ads
    Data Analysis
    Biostatistics
    Marketing Analytics
    Econometrics
    Neural Network
    Time Series Analysis
    Tableau
    Python
    SAS
  • US$35 hourly
    Statistician with a large amount of experience in R and a small amount in SQL/Python. Good with graphics, GLMM's, Bayesian modeling, GBM's, bootstrapping, predictive and explanatory modeling. Trying to create a startup and doing this for (the other kind of) bootstrapping purposes.
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    Statistical Infographic
    Modeling
    Statistics
  • US$30 hourly
    Machine learning, mathematical modeling, and data analysis are the core of my skills. I can use existing techniques of diverse environments and easily adapt to different environments and frameworks. I can use these techniques in a wide range of applications, which include: radar image processing (SAR images), face recognition, natural language processing, marketing problems via GAMLSS, and remote sensing in Medicine (I took part in an awarded publication on this subject). Usually, I will ask you to describe your problem and your desired method of solution, if there is one. I can provide novel solutions that the client might not be aware of, and I usually bring this up during meetings and briefings if convenient. When not working in a team, I am very comfortable being the one to translate the practical situation to the mathematical setting and then present my solution, so feel free to contact me if all you got is a problem without a hint about the solution. I also enjoy very much discussing the solution with the client. Timely communication is important since I work a particularly demanding job as a teacher/researcher. It is very important to let you know that I am only available outside my daily work hours, which go from 08:00 to 17:00 (GMT-3 timezone) and weekends.
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    R Shiny
    Web Scraping
    Natural Language Processing
    Statistical Infographic
    Statistical Programming
    Problem Solving
    Neural Network
    pandas
    Machine Learning
    Statistical Analysis
    Statistics
    Data Analysis
    Data Analytics
    Python
  • US$150 hourly
    I have extensive experience conducting analyses in R, SPSS, AMOS, JASP, and jamovi. I also use R for visualizations, and can make R Shiny apps. I am experienced with descriptive statistics, t-tests, correlations, regression (linear, multiple, logistic, lasso, etc.), ANOVA, mediation, moderation, principal components analysis, factor analysis, structural equation modeling, discriminant analysis. I also can create a wide range of figures (e.g., box plots, bar charts, heatmaps, histograms, scatter plots, biplots, etc.), depending on what is required. My interests and previous experience include -omics research (e.g., metabolomics, lipidomics, etc.), psychology, cognitive neuroscience (including a lot of EEG data), and sports analytics. I have a Ph.D. in psychology, and currently work in statistics.
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    Data Analysis
    IBM SPSS
    Mathematical Modeling
    Bayesian Statistics
    Academic Writing
    AP Style Writing
    Statistics
    Scientific Research
    Analytics
    Data Visualization
    Statistical Analysis
    Quantitative Analysis
  • US$75 hourly
    Please also see my blog: jiddualexander.com I'm a data scientist / analyst and an expert R programmer. I am strong with ggplot (ggplot2 data visualisation) and I am also a Shiny App developer. I can create custom dashboards for your data with intelligent analytics and interactive graphics. I program in R 6 days a week and I am very confident with all aspects of a data analysis project. I use mostly the very powerful packages created by Hadley Wickham (data import, cleaning and tidying (tidyr), manipulation (dplyr), visualisation (ggplot2) and reporting (Shiny)). The list of online certificates (below) is a good indication of the focus of my skills. To understand the power of these tools for creating dashboards I suggest you take a look at RStudio's Shiny gallery (shiny.rstudio.com/gallery/). I have participated in the Master R Developer Workshop by RStudio, thaught by no other than Hadley Wickham himself. My expert knowledge in R extends to high quality functional programming, package building, meta-programming and more. I have a Master Degree in Theoretical Physics from Sussex University (UK) and very strong understanding of analytics and machine learning, including neural networks (which I studied at Uni), support Vector machines, RandomForest, Principal Component Analysis (PCA) and much more. Including the tools to train machine learning models I also have a fundamental understanding and set of tools to apply the correct models for specific situations.
    vsuc_fltilesrefresh_TrophyIcon R
    Data Modeling
    Data Cleaning
    Data Visualization
    ggplot2
    Data Analysis
    Artificial Neural Network
    Data Science
    Machine Learning
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R vs. Java vs. Python: Which Is Right for Your Project?

When it comes to data science, there’s no one best programming language. There are a few standouts, however, each with its own specialties, as well as packages, libraries, and extensions that further enhance their capabilities.

In this article, we’re going to take a closer look at three of the most popular languages used by data scientists: Java, Python, and R. You’ll learn the basics of each, as well as how to tell which one is right for your data needs.

R: beloved by data scientists

Originally developed by statisticians as an open-source alternative to expensive suites of statistical software like SAS and MATLAB, R is one of the most popular languages for data analysis. It’s been likened to Excel on steroids, able to sift through reams of data, execute sophisticated analyses, and produce publication-quality graphs and tables. What makes R special? In short, it’s a tool built with data analysis in mind.

As data science has become critical to many businesses, R’s popularity has skyrocketed. Organizations as large and diverse as Google, Facebook, Microsoft, Bank of America, and the National Weather Service have all turned to R for reporting, analysis, and visualization.

A key component of R is that, unlike object-oriented programming languages like Java or Python, R is a procedural language, meaning it relies on a series of step-by-step subroutines to execute a programming task. The key difference here is that R uses procedures to operate on data, where object-oriented programming bundles procedures and data together as parts of objects. The advantage of procedural programming is that it gives clear visibility into complex operations with lots of dependencies, which can be important for many data analysis tasks. The tradeoff is that this often requires more lines of code than object-oriented languages.

Another benefit of R? It’s supported by a vibrant community of developers, especially academic statisticians and data scientists.

Java: speed at scale

Java is powerful, portable, and scalable, which makes the platform perfect for building enterprise-scale applications and supporting rapid growth. Java also includes many tools, collectively known as the Java Platform. This robust, open-source development environment includes libraries, frameworks, APIs, the Java Runtime Environment, Java plug-ins, and the Java Virtual Machine (JVM). Taken together, these tools simplify coding with Java and support development at every level, giving developers everything they need to build Java web systems and applications.

Java’s speed allows it to outperform other languages and frameworks, which is a big part of why it’s so well suited to large-scale applications. These performance gains are what prompted Twitter to shift its search engine to Java from Ruby on Rails and move more of its back-end stack to the Java Virtual Machine.

Another key component of Java is that it comes as close to being 100% object-oriented as you can get. With that comes all the benefits of object-oriented programming, from ease of development to modular software to flexibility and extensibility. As one of the most widely known programming languages, it’s easy to find and hire talented developers. What’s more, Java’s massive community of developers means that there’s lots of excellent documentation around.

Python: built for flexibility

Like Java, Python is built to handle high-traffic sites. It’s fast and efficient, with an emphasis on code readability. Python’s motto is “there should be one—and preferably only one—obvious way to do it.” That can mean there’s a bit of a learning curve as developers learn the ins and outs of Python syntax, but the upside is an ability to express concepts with fewer lines of code than would be possible in languages like C++ or Java.

Python’s other great strength is an extensive set of libraries that allow it to perform a wide array of tasks. In particular, the libraries NumPy and matplotlib enable Python to perform many of the analysis and plotting functionalities of MATLAB. These libraries have since been built upon by a number of other libraries that extend Python’s functionality even further.

In short, Python represents a compromise between R and Java, combining the sophistication of the former with the speed and scalability of the latter.

Which language is right for your data needs?

The short answer is that it depends on the kind of work you’re trying to do. A good rule of thumb might be if your work is closer to mathematics and statistics, R is probably your best bet. If your work is closer to programming, go with Python, and if you’re building enterprise-size products, take a look at Java. That said, many data scientists are increasingly turning to combinations of languages that allow them to take advantage of the individual strengths of each.

R

Great For:

  • In-Depth Statistical Analysis. Given that R was developed by and for statisticians, it’s no surprise that R is ideally suited to in-depth statistical analysis, whether you’re working with sensor data from an IOT device or elaborate financial models. What’s more, it’s very well supported by the statistics community through the CRAN repository, which contains literally thousands of packages that enable you to perform more elaborate analysis and visualization tasks.
  • High-Quality Reporting. Well-produced images convey more than numbers alone, and R places a great emphasis on easily producing high-quality graphs and charts. On top of that, its basic capabilities can be extended with a number of packages, including ggplot2, ggvis, googleVis, and rCharts. The Shiny framework also allows you to turn those visuals into interactive web applications.

Not Great For:

  • Performance. R was designed with data scientists in mind, not computers. As such, R is considerably slower than Python or Java.
  • Creating large-scale data products. In these instances, data scientists will often prototype in R and then switch to a more flexible language like Java or Python for actual product development.
  • Ease of Learning. If your background is in math or statistics, R’s array-oriented syntax can make implementation relatively straightforward. If you have programming experience, however, this approach is likely to seem counterintuitive.

Java

Great For:

  • Excellent Performance on Large-Scale Systems. Java’s speed makes it best for building large-scale systems. While Python is significantly faster than R, Java provides even greater performance than Python. Speed and scalability are why Twitter, LinkedIn, and Facebook rely on Java as the backbone of their data engineering efforts.
  • Faster Development Time. The Java Virtual Machine (JVM) is a great environment for developing custom tools quickly. The programming language Scala runs on JVM and is popular with data scientists for its combination of object-oriented and functional programming.

Not Great For:

Statistical modeling and visualization. Between these three languages, Java is definitely the least suited to hardcore analysis. Though packages do exist to add some of these functions, they’re neither as advanced nor as well supported as the ones you’ll find for Python and R.

Python

Great For:

  • Workflow Integration. Python’s flexibility makes it a popular choice for developers who need to apply statistical techniques or data analysis in their work, or for data scientists whose tasks need to be integrated with web apps or production environments. If you’re looking for a single tool to manage your entire data-related workflow, Python is a great option.
  • Machine Learning. The combination of specialized machine learning libraries (like scikit-learn, PyBrain, and TensorFlow) and general purpose flexibility makes Python uniquely suited to developing sophisticated models and prediction engines that plug directly into the production system.

Not Great For:

  • Highly specialized data tasks. Though the Python community is catching up, there are still hundreds of R packages that have no Python equivalents. If you’re looking for very specific capabilities, you might be better off with R.

Hiring a data scientist?

Now that you understand the differences between some of the major languages in data science, who do you need to set up and maintain your data infrastructure? Data scientists come from a variety of backgrounds. Some specialize more in performing statistical analysis, while some are more focused on building products that interface directly with production systems. Explore data scientists on Upwork.

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