Hellen Kitheka
Data Scientist and Programme Monitoring, Evaluation and Learning (MEL) Specialist
Nairobi
Summary
Analytical and impact-driven professional with 5+ years’ experience in Data Scient and Programme Monitoring, Evaluation and Learning (MEL) in development finance with interest on the banking and financial services sector. Currently pursuing an MSc in Data Science, with hands-on skills in Python, SQL, NoSQL, Power BI, and R. Adept at designing data frameworks, analyzing large datasets, and transforming data into actionable insights. Demonstrated success in stakeholder engagement, Key Performance Indicator (KPI) reporting, financial forecasting, and dashboard creation—now applying these skills to predictive modeling, customer analytics, credit risk, and fraud detection in a data-driven environment.
Overview
7
7
years of professional experience
Work History
Assistant Manager
PricewaterhouseCoopers
Nairobi
07.2024 - Current
- Led digital data collection (Qualtrics) and analytics-driven monitoring across 10+ international development programs; implemented data frameworks aligned with KPIs and compliance standards.
- Developed Power BI and Tableau dashboards and automated reporting pipelines for program impact analysis and donor reporting.
- Collaborated with stakeholders to translate strategic goals into measurable data outputs, improving transparency and decision-making.
- Introduced cost-saving data audit methods, reducing redundant expenditure by 15% and integrated insights into funding proposals, increasing portfolio success rate by 25%.
- Developed and deployed automated analytics pipelines and Flask APIs for risk scoring and fraud detection simulations in financial datasets, demonstrating production-readiness and model integration capability.
- Built deep learning LSTM model enriched with sentiment analysis to forecast stock trends on the Nairobi Securities Exchange, showcasing the integration of NLP and time-series modeling in emerging markets.
- Engineered ETL workflows and modeled data warehouse schemas for efficient extraction, transformation, and visualization of banking KPIs and customer behavior.
- Conducted capacity building and user training sessions on data dashboard interpretation and model outputs for non-technical stakeholders.
- Implemented automated anomaly detection tracking as part of fraud detection pipelines for enhanced monitoring and performance evaluation.
Senior associate
PricewaterhouseCoopers
Nairobi
01.2021 - 06.2024
- Designed and implemented data frameworks and dashboards (Power BI, SQL) to monitor program and financial KPIs, reducing reporting time by 30–40% and improving decision-making transparency.
- Applied statistical analysis (SPSS, R, Python) and machine learning models (logistic regression, decision trees, random forest) to evaluate programme impact, predict customer churn, and assess loan default risk.
- Applied test-driven approaches and data validation techniques to ensure data quality and model accuracy.
- Led cross-functional stakeholder engagements and secured donor funding through data-driven proposal writing and performance forecasting.
Statistician & Data Analyst
Kenya National Bureau of Statistics
Nairobi
02.2018 - 12.2020
- Conducted quantitative analysis and evaluations for national programs using SPSS and R.
- Designed survey tools and executed field-level data quality audits, leading to improvements in data reliability.
- Provided strategic feedback to policy teams through insight-driven reports and data visualizations.
- Streamlined internal reporting systems, reducing turnaround time for data delivery.
- Applied test-driven approaches and data validation techniques to ensure data quality and model accuracy.
Education
Master of Science - Data Science
KCA University
Nairobi, Kenya 09.2023 -
Bachelor of Science - Applied Statistics with IT
Maseno University
Kisumu 08.2012 - 07.2016
Skills
-Data Science & Statistical Modeling (Python pandas, NumPy scikit-learn, matplotlib, seaborn, Excel, R, SQL, SPSS, Power BI, Tableau)
-Machine Learning & Automation (Logistic Regression, Random Forests, Decision Trees, Naive Bayes, Support Vector Machines (SVM), Clustering, Feature Engineering, Anomaly Detection)
-Model Deployment (Streamlit dashboards, Flask APIs))
-Big Data & Cloud (Basic knowledge of PySpark and Apache Spark (via self-study), Familiarity with cloud platforms (Google Cloud, AWS fundamentals – Coursera)
-Data Handling (Feature Engineering, ETL, Data Cleansing, Data Wrangling)
-SQL & Data Management (MongoDB, Hive, Pig, PySpark (learning))
-Data Visualization & Reporting(Power BI Dashboards, Business Intelligence Tableau Reports, KPI Presentations, Matplotlib, Seaborn)
-Data Engineering & Warehousing (ETL Pipelines, SQL for Data Extraction and Transformation, Hadoop, Scala, Data Cleaning, Schema Design (Academic Projects)
-Methodologies (Agile Delivery, PRINCE2, Test-Driven Analysis)
-Stakeholder Engagement & Communication
OTHER POSITIONS HELD
- May - July 2016, Industrial Attachment, Kenya Medical Research Institute (KEMRI)/CPHR
- Sep - Oct 2015, Evaluation Enumerator and Data Clerk, World Vision International, Mutonguni
- May - Aug 2015, Intern, Kitui County Treasury
SELECTED PROJECTS IN DATA SCIENCE
1. Power BI and Tableau Performance Tracking and Monitoring Dashboards
Designed and deployed live dashboards to track program performance tracking and monitoring indicators, financial disbursements, and real-time field data.
2. Telecom Customer Churn Dataset
Built a customer churn prediction model using Python, applying machine learning algorithms (Naïve Bayes, SVM, Logistic Regression, Decision Tree, Random Forest), with data preprocessing, exploratory analysis, and model evaluation to improve accuracy and support business decision-making.
3. Stock Market Prediction Using LSTM and Sentiment Analysis
Developed a hybrid deep learning model using Long Short-Term Memory (LSTM) to predict stock trends on the Nairobi Securities Exchange, integrating financial time series data with sentiment analysis from news and social media. Improved predictive accuracy over traditional models (ARIMA, GARCH) by capturing both technical patterns and investor sentiment.
4. ETL and Data Warehousing Mini-Project (SQL)
Designed and implemented an ETL pipeline using SQL to extract, transform, and load customer records into a normalized schema. Focused on banking customer segmentation and product performance analysis.
5. Transaction Anomaly Detection (PySpark, Academic Simulation)
Used PySpark to process simulated transactional data and detect anomalies via clustering. Demonstrated Spark-based processing on large-scale data as part of a cloud computing course project.
SEMINARS AND CONFERENCES
- Homa Bay International Investment Conference 2024
- Blue Economy Investment and Innovation Summit
Accomplishments
- Advisory Diamonds Awards in Digitizing Business - PricewaterhouseCoopers
- Public Speaking Program – Dress to Impress Group
TRAININGS AND WORKSHOPS
- Leading Teams Training Workshop
- Future Leaders Programme – Effective Enrollment Training
- Engagement Economics Training
- Future Leaders Programme- Effective Engagement Training
CERTIFICATIONS
- PRINCE2 Foundation and Practitioner Certified
- Certificate in Monitoring and Evaluation
- Diploma in PowerPoint, Excel, Data Literacy, Kubicle
- Diploma in Generative Artificial Intelligence
- Statistical Package for Social Science (SPSS), KESAP College
- Proposal Writing Skills for Rural Development Training, Tropical Institute for Sustainable Development.
Languages
English
Fluent
Swahili
Fluent
Interests
Networking
Travelling
Community Development
Reading
Young Women Empowerment
References
References available upon request.
Timeline
Assistant Manager
PricewaterhouseCoopers
07.2024 - Current
Master of Science - Data Science
KCA University
09.2023 -
Senior associate
PricewaterhouseCoopers
01.2021 - 06.2024
Statistician & Data Analyst
Kenya National Bureau of Statistics
02.2018 - 12.2020
Bachelor of Science - Applied Statistics with IT
Maseno University
08.2012 - 07.2016