Emmanuel Kiriinya

Emmanuel Kiriinya​ Data Scientist SUMMARY Data Scientist and Analytics Professional with experience working across SQL-based data systems, analytics, and applied modeling to generate operational and strategic insights. Experienced in data collection, cleaning, exploratory analysis, dashboarding, and predictive modeling using SQL, Python, Power BI, and Excel. Strong background in time-based trend analysis, scenario forecasting, and automation to support decision-making in resource-constrained environments. Adept at translating complex data into actionable insights for technical and non-technical stakeholders, with experience supporting cross-functional teams and policy-relevant reporting. SKILLS -​ -​ -​ -​ -​ -​ -​ Programming & Data Science: Python (pandas, numpy, matplotlib, seaborn, scikit-learn, TensorFlow), SQL (advanced queries, CTEs, window functions) Machine Learning & Time Series: Exploratory modeling, regression models, classification basics, time series analysis (trend analysis, rolling averages, seasonal decomposition, ARIMA, SARIMA, LSTM), scenario forecasting Business Intelligence & Visualisation: Power BI (data modeling, DAX basics, Power Query), interactive dashboards, time-based KPIs and trend reporting, Excel Databases & Data Management: Microsoft SQL Server, relational database design, data integrity controls, access management, backups and recovery Causal & Statistical Analysis: Impact evaluation, hypothesis testing, longitudinal analysis, feature engineering Data Products: Decision dashboards, analytical frameworks, data storytelling Field & Survey Data: Data quality validation, survey analysis, heterogeneous datasets EXPERIENCE Data Scientist – Data Science East Africa(DSEA), Nairobi Jun 2025– Present : Full-Time -​ Designed hypothesis-driven data validation and analytics frameworks that improved reliability of program and operational datasets by 30%, enabling more confident decision-making. -​ Built end-to-end Python and SQL pipelines to clean, integrate, and analyze multi-source datasets, including survey and operational data used for program monitoring. -​ Conducted exploratory and statistical analyses to identify drivers of performance variation across cohorts, supporting evidence-based program adjustments. -​ Translated complex analytical outputs into concise dashboards and narratives used by management to inform prioritization and delivery decisions. -​ Collaborated with technical and non-technical stakeholders to align analytical work with program theory and operational constraints. Data Analyst/Scientist – Ngeni Labs, Nairobi Jan 2024– May 2025 : Full-Time -​ Built and maintained longitudinal datasets from repeated survey and operational data collections, ensuring consistency, integrity, and analytical usability. -​ Automated recurring analyses using Python and SQL, reducing manual processing time by 40% and improving reproducibility of insights. -​ Developed Power BI dashboards that surfaced high-signal indicators for program performance, increasing stakeholder engagement with data by 40%. -​ Supported impact-oriented analysis by examining subgroup outcomes and contextual factors beyond population averages. -​ Documented analytical assumptions, data limitations, and interpretation guidance to support responsible use of results. Data Analyst – KTDA May 2023 –Sep 2023: Internship -​ -​ -​ -​ -​ Built 10+ interactive Power BI dashboards tracking production, sales, and costs, now used by managers. Automated 60% of manual reporting processes using Excel and SQL, cutting turnaround from 3 days to 1. Collaborated with department leads to define KPIs and develop data-driven performance tracking tools. Designed and implemented data cleaning scripts that improved accuracy of key production metrics by 30%. Trained staff on dashboard usage and Excel best practices to improve data literacy and adoption. EDUCATION Bachelor of Science ( Economics and Statistics with IT ), Maseno University- Nov 2020