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.

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

Biostatistician of 3 years with 13 years of collective data analysis experience and proven track record of delivering data-centered narratives (15 published articles) in diverse disciplines from -omics to healthcare research. My go-to tool is R/R-studio, I favor Bayesian methods, and I take pride in delivering expert-level services. Expert-level services: * Data management, analysis, and visualization * Review and editing academic writing (protocols, posters, abstracts, manuscripts, dissertation) * Study design consultation (power analyses, Bayesian operating characteristics) * 1:1 mentorship and training on R coding, research methods, project management, data management Skills: R/R-studio, Data analysis, Project management, Database development (REDCap expert), Dashboards (PowerBI) , Data wrangling, Bayesian methods, Monte Carlo Simulations, Causal Inference (propensity scores, standardization, difference-in-difference-DiD, synthetic controls) Credentials: * Practicing biostatistician that leads clinical trials, observation, and quality improvement studies in the area of oncology at a cancer institute * PhD in quantitative biology * 16 peer-reviewed publications in the areas of surgical oncology, medical oncology, quantitative genetics, evolutionary physiology, genomics, gene expression, and study design.

I’m Clinton, a Data Scientist with 8+ years of hands-on experience in data engineering, analytics, and automation. My focus is on creating reproducible, scalable, and impactful data solutions, from interactive dashboards to automated pipelines and predictive models. 💡 Core Expertise 🗺 Spatial & Geospatial Analytics - Advanced spatial workflows using R, Python, and Google Earth Engine - Poverty and vulnerability mapping using small area estimation and related methods - Disaster risk and impact modeling, including flood, drought, and displacement analytics - End-to-end geospatial data engineering, from data extraction and transformation to automated spatial pipelines and managing geospatial databases with PostgreSQL/PostGIS, and DuckD - Handling diverse geospatial data formats: GeoTIFF, shapefiles, GeoJSON, and satellite imagery - High-quality cartographic visualization and interactive mapping with R (leaflet, ggplot2), Python (geopandas, folium), Google Earth Engine Apps, and Shiny dashboards 📊 Data Visualization & Dashboards - Expert in R Shiny, Power BI, and Looker Studio — building interactive, data-driven dashboards that translate complex insights into compelling visuals - Specialized in high-performance Shiny apps, leveraging asynchronous programming (callr, future, mirai) and reactive optimization for smooth, scalable user experiences - Strong grasp of UI/UX design principles — crafting dashboards that are intuitive, visually engaging, and tailored to end-user needs - Custom branding and theming to align dashboards seamlessly with client identity and design guidelines - Skilled in advanced data visualization using ggplot2, plotly, and leaflet, combining aesthetic storytelling with analytical rigor - Integration of geospatial layers (maps, raster tiles, and dynamic spatial filters) into dashboards for location-aware insights - End-to-end dashboard automation and deployment, including: Continuous integration with GitHub Actions, Docker, and webhooks - Secure hosting via Shiny Server, ShinyProxy, or cloud-based containers - Expertise in data pipeline integration, connecting dashboards directly to live databases (PostgreSQL, DuckDB, APIs) for automated updates and reproducibility - Full dashboard deployment on Shiny Server / ShinyProxy deployment, and CI/CD integration ⚙️ Data Engineering & Automation - End-to-end pipelines using R, Python, and Bash scripting - CI/CD with GitHub Actions, Docker, and webhooks - Async workflows with callr, future, and promises - Databases: PostgreSQL, MySQL, SQLite, and DuckDB 🤖 Machine Learning & MLOps - Predictive modeling with xgboost, caret, scikit-learn, and TensorFlow - Reproducible model management - Automated retraining and REST API integration 🌍 Trusted by Global Organizations I’ve supported data-driven decision-making for organizations such as UNICEF, FCDO, IFAD, CGIAR, and the Green Climate Fund, delivering projects spanning poverty mapping, forest monitoring, displacement analysis, and renewable energy modeling. 🤝 Why Work With Me 1. I listen first: to understand your goals and challenges clearly. 2. I collaborate transparently, providing regular updates and clear timelines. 3. I deliver reliably: production-ready, efficient, and well-documented work.

I turn messy, high-stakes data into decisions people can act on. Over 15+ years and 66 Upwork contracts (~4.9/5 stars across rated jobs, 84% perfect 5.0s), I've built my practice on one promise: you get a clear answer, a tool your team can actually use, and plain-English communication throughout. What I do best: * Interactive R Shiny dashboards and analysis platforms: 12+ shipped, including a 20+ package bioinformatics platform and a no-code causal-inference tool for pharmaceutical analysts * Machine learning and predictive modeling: injury prediction for an NFL franchise, mortgage default risk, game simulation * Statistical analysis: hierarchical Bayesian modeling, MaxDiff and survey analytics, meta-analysis, causal inference * R package development: a production package built over a 952-hour flagship engagement, plus a released CRAN package * Quantitative finance: DCC/GARCH modeling, asset allocation, backtesting frameworks Domains I know well: healthcare and EHR data, bioinformatics and genomics, finance and trading, marketing analytics, survey research, and sports. How I work: independently, end to end. Most clients hand me a problem, not a spec. I scope it, deliver in agreed milestones, and explain the results so non-technical stakeholders can make the call. That approach is why most of my work is repeat business, and why "Committed to Quality" and "Clear Communicator" are my two most-endorsed client tags. M.S. in Bioinformatics from Johns Hopkins. Co-author on 8 peer-reviewed papers. US-based native English speaker. If you have data that should be driving a decision and isn't yet, let's talk.

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.

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.

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).

I work on data integration, reconciliation, validation and reporting automation, mainly with operational data coming from multiple sources. I usually get involved when totals do not match, KPI definitions are unclear, or reporting depends on repetitive manual work. My work includes: * multi-source data integration * data validation and reconciliation * KPI and reporting logic checks * reporting automation * data cleaning and standardization * R/Shiny analytical applications * reproducible workflows and documentation Main tools: R, Shiny, SQL, tidyverse, R Markdown, Excel, REST APIs, CSV/JSON and Git. Recent work includes integrating and validating more than 59,000 appointments and 54,000 patient records for a multi-location US dental group, building a multi-bank reconciliation workflow with configurable matching rules, and consolidating multi-year real estate data into clear comparative reporting for business decision-making. I document assumptions, validation rules and unresolved issues so the workflow can be reviewed, maintained and updated later.