Lewis Muguna

Lewis Muguna

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Data Analyst | Data Scientist | Data Engineer
Nairobi County, Kenya

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Full-time jobs
Flexible work
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Open to unpaid internships

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Résumé


Jobs verified_user 0% verified
  • Braintrust
    Data Analyst
    Braintrust
    Mar 2025 - Current (1 year 3 months)
    • Designed and maintained end-to-end data solutions for diverse clients, utilizing Python, SQL, and Scala to build automated pipelines and train predictive models. • Partnered with product, engineering, and business teams to frame questions, define metrics, and embed real-time outputs in operational services. • Interpreted patterns, validated assumptions, and guided strategic decisions through intuitive dashboards and self-serve explores in Tableau and Looker Studio.
  • Q
    Data Analyst
    Qubiten
    Jan 2023 - Current (3 years 5 months)
  • Q
    Data Analyst
    Quebec
    Jan 2022 - Jan 2023 (1 year 1 month)
Education verified_user 0% verified
    Projects (professional or personal) verified_user 0% verified
    • B
      B2B SaaS Analysis Using Customer Data (BigQuery & Looker Studio)
      Apr 2025
      This project focuses on analyzing customer behavior, churn risk, and revenue generation for a B2B SaaS company using various advanced data science techniques and tools. The objective is to uncover insights that can optimize customer acquisition, retention strategies, and revenue generation by leveraging the power of SQL, BigQuery, Looker Studio, and predictive modeling.
    • D
      Data Analysis: Customer Segmentation and Behavior Analysis (R Studio)
      Apr 2025
      This project focuses on customer behavior analytics using R in R Studio, exploring the relationship between TotalPurchase, Frequency, and Customer Lifetime Value (CLV) through exploratory data analysis and correlation testing. Visualizations include bar graphs and scatterplots, supported by statistical metrics (correlation coefficients and p-values) to uncover actionable insights.
    • B
      Business Intelligence (BI): Sales Forecasting Dashboard (Databricks)
      Apr 2025 - Current (1 year 2 months)
      This project demonstrates a comprehensive sales data analysis using SQL within Databricks on Microsoft Azure. The analysis covers product-level revenue, units sold, store performance, and geographic trends. A robust ETL pipeline was developed in Databricks to ingest and process transactional sales data across countries and stores. Key business insights were visualized via interactive dashboards to support strategic decision-making.
    • F
      Fraud Detection and Financial Transaction Analysis (Snowflake, Machine Learning, and Tableau)
      Apr 2025
      This project showcases advanced SQL, Snowflake, and Tableau skills to analyze financial transactions for fraud detection and customer insights. Using Snowflake for data warehousing and SQL for data transformation, I built a robust ETL pipeline to process and stage transaction data. Key analyses include customer segmentation, fraud risk scoring, and transaction breakdowns. I developed interactive Tableau dashboards to visualize customer spending behavior and fraud risks. This project optimized fraud prevention, enhanced customer targeting, and improved financial operations through actionable insights, leveraging advanced analytics, data visualization, and cloud data infrastructure.
    • S
      Sales Forecasting and Marketing Optimization (Python, Oracle, Machine Learning, and Power BI)
      Apr 2025 - Current (1 year 2 months)
      This project showcases data science techniques and business intelligence strategies to optimize sales forecasting and marketing efforts using state-of-the-art tools and technologies. By leveraging Python for Data Science, Machine Learning, and Oracle for data storage and processing, the project develops an end-to-end sales prediction pipeline. The pipeline includes crucial steps such as data preprocessing, feature engineering, and model training, enabling market effectiveness.
    • G
      Google Ads Campaign Optimization Using Amplitude Analytics
      Apr 2025
      This project utilizes Amplitude, a powerful product analytics tool, to optimize Google Ads campaigns through detailed analysis of user behavior and ad performance across platforms like Google, YouTube, and Google Display Network. By tracking key metrics such as clicks, conversions, cost, impressions, and interactions, we identify areas for improvement in targeting and engagement. Skills & Tools: Product analytics, web analytics, Marketing analytics, Amplitude, and data visualisation.