Graduate from a top-rated school in Paris in Data Science with a research background in physics. More than 3 years of experience as a data analyst and R shiny developer in different areas (Healthcare, Energy Start-up, Decathlon E-commerce, …). Today, my missions as a freelancer are to automate data analysis, data science & machine learning models through dashboarding with R Shiny. I also help my clients by avoiding the repetitive tasks that take up their time every day (Automatic report generation with R Markdown, …). In parallel, I work on part-time contract as a data analyst & R shiny Developer for Decathlon Belgium. As a data visualization expert, I have a good mastery of highcharts, one of the best charting libraries on JS. I have also mastery of some BI tools, mainly Tableau and Google Data Studio. I am available to discuss your needs. ''' You want to see more about my latest built shiny apps? Please copy/paste in your navbar my portfolio link: ahmedjou.datarmy.com ''''

I build custom R Shiny dashboards, AI-assisted data tools, and web applications that help teams explore data, automate reporting, and make better decisions. With 60+ completed Upwork projects, 1,100+ hours, 100% Job Success, and Top Rated status, I specialize in turning complex data, Excel files, research workflows, and business processes into clean, interactive tools that are easy to use and maintain. I can help with: • Custom R Shiny dashboards and web apps • AI-assisted dashboards, chatbots, and data exploration tools • OpenAI/API integration inside Shiny apps • Interactive charts, tables, maps, and filters • Clean UI using CSS, JavaScript, HTML, bslib, and shinydashboard • R Markdown, Quarto, and automated reports • Data cleaning, transformation, and visualization • Database-connected Shiny apps • Debugging, refactoring, and improving existing Shiny apps • Deployment support and app maintenance Clients usually work with me when they need more than a basic dashboard. I can help plan the app structure, build the reactive logic, improve the UI, clean the data workflow, add useful AI features, and make the final app easier for users to understand. I have worked on Shiny apps for business dashboards, research tools, scheduling systems, economic models, flow cytometry data, maps, CRUD apps, AI-assisted tools, and data visualization platforms. I was also a Shiny Contest finalist, which reflects my focus on building useful, polished, and well-designed Shiny applications. Please note: I do not take academic assignments, exams, or homework projects. If you need a reliable R/Shiny developer for a dashboard, data app, AI-assisted workflow, or reporting tool, I would be happy to help.

I'm a self-taught R programmer with a strong research background. I did my PhD and my time as a faculty member in Quaternary Geology, which gave me valuable experience with complex data modelling, visualization and interpretation (both quantitative and qualitative). I love learning, take pride in finding new and creative solutions to problems, fixing broken things and explaining complex ideas in very simple terms. I thrive by helping others.

Ready to dive into your data deeply Make data analysis and predictive modelling Marketing and business domains are preferred Proficient in customer and investments analytics ✅ EXPERT-VETTED TOP 1% ON UPWORK 🚻 Customers and growth analytics Calculation different customer KPI like LTV Segmenting customers by using the RFM method Customers cohorts analysis to detect churn Scoring customer and revenue churn risks Predicting dates and prices of future orders Modeling prices and revenue flow scenarios Analyzing user behavior on social media 🛒 Products and inventory analytics Forecasting stock-out events to minimize lost of sales Planning assortment based on ABC & XYZ analysis Assessing product competitiveness on the market Market basket analysis based on association rules Product sentiment analysis based on social media data 🏦 Venture capital investment analytics Deep understanding of crunchbase data source Scoring startups' success, multiples, and time of exit Startup market analysis and trends insights Modelling investment deals processes Design due diligence recommendations 📶 Trading analytics Designing and verifying trading strategies Modelling reflexive behavior strategies Recognizing threat patterns in trading data Detecting anomalies and outliers in trading data Managing trading deals and assessing associated risks Assessing fraud risks in trading and investment activities Algorithmic trading strategies design for crypto market 🚀 Google Analytics Defining click-through-rate drivers Assessment listings search sort relevance Scoring and ranking website users' engagement Calculations of normalized discounted cumulative gain 🧪 Clinical Trials Analytics Design R Shiny dashboards for analytical results reporting Redesign legacy R and R Shiny code to have more robust apps TECH STACK 🔧 Core Languages Python (primary) – ML systems, data engineering, APIs, AI and LLM R (advanced) – R Shiny apps, analytics, reporting, statistical modeling SQL (expert) – 20+ years, complex analytics & data modeling 🎛 Data Science & Machine Learning Data analysis: tidyverse, data.table, lubridate Modeling: tidymodels, caret, mlr3, parsnip, broom Tree-based models: ranger, randomForest, xgboost, catboost Time series: forecast, prophet, tidyverts, xts, zoo NLP: tidytext, quanteda, sentimentr, stm Quant finance: quantmod, quantstrat Pharma analytics: pharmaverse, rtables, admital, tidytlg 👨‍💻 Data Apps, APIs & Reporting Dashboards: shiny, shinydashboard, bslib, shinyjs App frameworks: golem, rhino, teal Tables: DT, reactable, gt, flextable Reporting: RMarkdown, bookdown, LaTeX Auth: shinymanager, shinyauthr Mobile apps: shinyMobile APIs: plumber 💾 Data Engineering & Storage Databases: RMySQL, RODBC, bigrquery Cloud & formats: aws.s3, jsonlite, feather, openxlsx Distributed: sparklyr, SparkR, h2o Platforms: Databricks, Snowflake, Palantir Foundry, AWS 📶 AI, LLMs & MLOps LLM apps: ellmer, querychat, shinychat,mini007 Shared: Experiment tracking: MLflow 🤹 Visualization Core: ggplot2, ggpubr, ggmap Networks: igraph, ggnetwork, geomnet Hierarchies: treemap, data.tree JS integrations (via R) plotly.js, d3.js, highcharts, leaflet, networkD3 ⚙️ Software Engineering Packaging: devtools, renv, packrat Performance: Rcpp, RcppParallel, microbenchmark Parallel computing: foreach, doParallel ⏱️ Trading & Quant Systems Research & backtesting: quantmod, quantstrat

Hello—I’m Matt Simonson, a data analyst and R Shiny developer who specializes in transforming complex datasets into clear, actionable insights for strategic decision-making. Consulting Experience (Bada Consulting, January 2025 – Present): My recent projects include building sophisticated applications that streamline data-driven decisions: • Land Pricing & Clustering App: Automatically processes parcel CSVs, clusters properties using Gaussian-mixture models, and generates precise acreage-tier price forecasts in seconds—dramatically reducing underwriting time from hours to minutes. • UPC Forecasting & Optimal Pricing App: Fits robust demand models, visualizes uncertainty with 95% confidence ribbons, and identifies the most profitable price points for individual SKUs, helping clients optimize pricing for over 100 products. • Medical Billing Tier Escalation Model: Developed an automated R module that ranks over 50,000 billing cases nightly, strategically escalating the riskiest 20% and improving recovery outcomes through dynamic, data-driven rules. Enterprise Experience (Abbott Laboratories, 2019 – Present): At Abbott, I leverage advanced analytics to streamline critical processes and enhance compliance across an €80M medical device portfolio: • Automated data transformations involving millions of data points, significantly improving reporting speed and accuracy. • Developed interactive R Shiny dashboards that track global inventory and forecast system utilization, aiding strategic planning at key distribution centers. • Led complex, cross-functional analytics initiatives that have improved forecasting accuracy, reduced operational inefficiencies, and ensured regulatory compliance. What I Offer: • Comprehensive R Shiny solutions: End-to-end design including user interface, server logic, secure authentication, and seamless deployment (Docker/AWS). • Advanced econometric and machine learning models for pricing optimization, demand forecasting, and claims analytics. • Clear, maintainable code accompanied by thorough documentation and tailored training for seamless transition and long-term client success. Tech Stack: • R (tidyverse, plotly, DT, estimatr, mclust, shiny, caret), Python (pandas, numpy, scikit-learn, matplotlib, seaborn, streamlit), SQL, Tableau/Power BI, Excel. If you’re seeking a partner who can rapidly prototype analytics tools, collaborate closely with stakeholders, and deliver robust, data-driven solutions—let’s connect.

I have worked for a wide range of clients on projects that focus on machine learning, dashboard creation, web scraping, statistics, finance, medicine, bioinformatics, and much more. Contracts ranged from small independent projects to building dashboards for fortune 500 companies. Projects vary greatly, but machine learning, data analysis, statistics, and creating nice visuals and interactive dashboards are common themes. I have been programming in R for over 20 years.

Associate Director-level data professional with 10+ years of experience turning complex data into actionable insight across analytics, product operations, and AI-driven solutions. I specialise in end-to-end data workflows — from database architecture and SQL optimisation to interactive dashboards and automated reporting pipelines. My toolkit includes SQL, Power BI, R, R Shiny, and Python, and I hold an MSc in Data Analytics backed by a First Class BSc in Computer Software Engineering. Recent highlights include: ∙ Building R Shiny dashboards to replace legacy manual processes, dramatically reducing turnaround time and human error ∙ Designing and optimising SQL procedures for performance at scale ∙ Delivering analytics solutions aligned to business KPIs in regulated, enterprise environments I bring the rigour of a senior corporate role to every freelance engagement — clear communication, structured delivery, and a genuine focus on outcomes rather than outputs. Whether you need a one-off dashboard, a data pipeline overhaul, or ongoing BI support, I’ll deliver work that’s clean, documented, and built to last.

👋 Hi, I’m Joseph Mburu Nuthu — a Certified Data Analyst and Statistician with over 6 years of experience helping students, researchers, and professionals make sense of their data through quantitative research and statistical analysis. Whether you need support with your academic thesis, dissertation, survey analysis, or a professional research report, I’m here to deliver precise, reliable, and well-documented results. 🎯 What I Offer: Survey Design & Analysis – Crafting reliable questionnaires and performing descriptive and inferential analysis. Statistical Analysis – T-tests, ANOVA, correlation, chi-square, regression, reliability testing, factor analysis, and more. Academic Research Support – Full assistance with methods, analysis, and results chapters following APA, Harvard, and other styles. Data Cleaning & Preparation – Organizing and validating your dataset for accurate analysis. Interpretation & Reporting – Clear explanation of findings with visual aids such as charts and tables. 🧪 Tools I Use: SPSS, R, RStudio, SAS, Minitab, Excel, JAMOVI, JASP, SmartPLS, AMOS, STATA 📚 Fields of Expertise: Public Health, Psychology, Education, Business, Economics, Environmental Studies, and other social sciences. 💡 Why Clients Choose Me: Strong academic and applied statistics background (PhD in Statistics) Timely delivery and clear communication Accurate, publication-ready outputs Proven track record on Upwork with consistent 5-star reviews 📈 Whether you're a student working on a dissertation, a researcher analyzing survey data, or a professional needing expert statistical support, I’m ready to help you turn data into insight. Let’s collaborate and make your research a success!

For more than a decade, I utilize the R and Python programming languages to process, visualize and extract information from data and for almost five years for Geospatial analysis. I'm the author / maintainer of R packages (I've submitted more than 10 to CRAN). You can view my Github profile at the following weblink: github.com/mlampros I work with R and Rstudio on a daily basis. I can work with machine learning algorithms based on almost all CRAN, Github or Gitlab repositories. I can utilize visualization R packages such as ggplot2, plotly, tmap, leaflet, mapview. I can create shiny applications (shiny.rstudio.com/gallery/) and report my results in .pdf, word, .html or any other available format using Rmarkdown. Moreover, I'm capable of using the hybrid 'Rcpp' and 'RcppArmadillo' R packages to improve the efficiency of R code and the Keras and Pytorch deep learning libraries for regression, classification, object detection or image segmentation (with or without pre-trained models).

Your project booster! I'm a fast working dynamic coder and statistician. For research projects, marketing, data management and coding - I bring 15 years of experience consulting to do FAST, REAL work. My daily work is data analysis, programming and research design in academic and corporate settings. building predictive models, leveraging data insights with machine learning and AI. I also run my OWN PERSONAL RESEARCH server, and have set up plenty of Qualtrics, RedCap and other survey and research systems. Statistics: SPSS, JASP, R, Exploratory analyses, Descriptive Statistics, Regressions, ANOVA, MANOVA, Correlations, t-tests, PCA, Bootstrap, Permutation Tests, Interpreting p-values and effect sizes. Machine Learning, Tidymodels, pytorch, GITHUB, git. R Programming: Data mangement, cleaning, extraction, custom scripting, tidyverse, ggplot2, Visualizations: Scatterplots, Time-series, Dotplots, Boxplots, Heatmaps, Distributions, PCA Technologies: AI, github, copilot, gemini, LLMs, prompts, Excel Research Writing: Interpreting results, validating conclusions, writing results in APA style, high quality scientific writing. More about me: I've worked in multiple scientific areas of research, have published articles and reviews, and have worked as a statistics instructor for university classes as well as a graduate mentor, making me an ideal candidate to help you build your own understanding of data analytics. My academic background in Cognitive Science focused on decision making, artificial intelligence, language and performance prompted by theoretical concepts from complex systems and neural networks. I utilize methods of distribution modeling, fractal analysis, timeseries analysis, complex regression, algorithmic model selection and general statistics to analyze data. I have proficiency in MatLAB, SPSS and R.