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Mercy CHERONO

@mercycherono

MSc Data Science | Excel, Python & Linux/Bash expert. Passionate about LLM AI annotation, prompt engineering & response evaluation.

Kenya

Message

What I'm looking for

I’m looking to leverage my Python scripting, Linux/Bash automation, SQL, and Power BI skills to deliver customer-focused analytics, BI dashboards, and AI evaluation work in digital financial services — building predictive models, automating data pipelines, and conducting LLM response annotation and prompt engineering that drive accurate, timely decisions.

I’m a data science professional with an MSc in Mathematical Sciences (Data Science, Distinction) from AIMS and a BSc in Actuarial Science (First Class Honours). I specialize in automating data workflows, building insightful dashboards, and turning complex datasets into clear business decisions.

In my roles at Britam Insurance and Minet Kenya, I processed policies and performed reconciliations under tight TATs while maintaining 100% accuracy in corporate schemes and member files. As a Data Analytics Intern at Mega Wholesalers, I developed Python scripts for automation of data cleaning and forecasting pipelines, directly supporting faster last-mile delivery decisions. I also built a complete Python automation pipeline (using pandas + openpyxl) that cleaned a 209-country COVID-19 dataset with 819 missing values, engineered new risk features, and generated professional KPI dashboards.

Proficient in Python (scripting & automation), SQL, Power BI, R, Excel, Linux Command Line / Bash Shell (proficient since 2022 via ALX), and statistical modeling. I’m especially excited about remote LLM AI Annotator / AI Evaluator roles where I can apply my skills to prompt engineering, side-by-side response comparison, trajectory creation, and improving AI model performance in digital financial services or tech companies.

Experience

Work history, roles, and key accomplishments

Business Processing Assistant

Britam Insurance

Mar 2024 - Dec 2025 (1 year 9 months)

Processed new and renewal policies in line with SLAs, managing endorsements, scheme reconciliations, and member/benefit setup for corporate and retail schemes. Coordinated medical card requests and maintained client records to meet turnaround times.

SLA Data Reconciliation Endorsement Medical Card Processing

Data Analytics Intern

Mega Wholesalers Ltd

Oct 2023 - Dec 2023 (2 months)

Analyzed large datasets using Python and SQL to support last-mile delivery optimisation and sales/procurement forecasting. Applied data analytics to generate projections and operational insights for decision-making.

Python SQL Data & Analytics Forecasting Sales Forecasting Data Cleaning

Medical Underwriter

Minet Kenya

Apr 2022 - Aug 2022 (4 months)

Underwrote new business and renewals, handling endorsements, upgrades, and cancellations while adhering to policy guidelines and producing debit/credit notes on schedule. Cleaned and reconciled membership lists and monthly statements against internal systems to ensure correct coverage.

Renewals Management Risk Assessment

Medical Underwriting Intern

Minet Kenya

Aug 2021 - Apr 2022 (8 months)

Supported underwriting for new business and renewals, including debit/credit note preparation, membership list clean-ups, and medical card updates. Assisted with client record maintenance and dispatching during policy administration.

Underwriting Support Membership List Cleanup Medical Card Updates Policy Administration

Education

Degrees, certifications, and relevant coursework

African Institute for Mathematical Sciences (AIMS)

MSc in Mathematical Sciences, Data Science

2022 - 2023

Grade: Distinction

Completed an MSc in Mathematical Sciences (Data Science), graduating with distinction. Completed a master’s dissertation on a non-parametric approach to determine the probability of first success.

Karatina University

BSc Actuarial Science, Actuarial Science

2017 - 2021

Grade: First Class Honours

Completed a BSc in Actuarial Science, graduating with first class honours. Completed an undergraduate thesis using logistic regression to analyze factors contributing to low life insurance uptake among Kenyan youths.