Jackline Ngenia

Jackline is a result oriented Data Scientist with experience in Python and R Programming Languages, predictive modeling, reporting and analytics in various sectors. She has strong knowledge of the techniques of probability, statistics and mathematics. She is experienced in working on real-time statistical data using Data Analysis, Excel, R and Python while possessing solid quantitative SQL skills. In addition, she is proficient with Machine Learning. 

She is passionate about developing new skills and building lasting professional relationships for self growth and organizational achievement.

She aims to achieve high career growth through a continuous learning process and keep herself dynamic, visionary and competitive with the changing scenario of the world.

Data Scientist (2022 - Date)

1. Utilizes data analysis techniques to score and set lending limits for small businesses, contributing to more accurate risk assessment and lending strategies.
2. Spearheads data cleaning initiatives, ensuring the accuracy and integrity of data used for analysis and decision-making.
3. Creates comprehensive Tableau reports for data visualization, aiding in easy comprehension and decision-making for stakeholders.
4. Transforms complex data sets into insightful visualizations that assist in identifying trends, patterns, and areas for optimization.
5. Develops and implements machine learning models for predictive analytics, enabling data-driven decision-making and driving business value.
6. Collaborates closely with cross-functional teams, including colleagues from various departments, to gather insights, share findings, and contribute to overall business objectives.
7. Develops innovative solutions to challenges related to data quality, model accuracy, and process efficiency, resulting in streamlined workflows and improved outcomes.
8. Contributes to the company's bottom line by providing data-driven insights that inform strategic decisions, leading to optimized lending strategies and improved business performance.

Skills: Git · Predictive Modeling · Predictive Analytics · Exploratory Data Analysis · Tableau · PostgreSQL · MySQL · Statistical Data Analysis · Python (Programming Language) · Machine Learning · Data Visualization · Data Cleaning

Machine Learning Engineer (2022 - Date)

Project name: Facilitating access to financial services for underserved populations in Africa

I collaborated in the Omdena AI with the impact startup Toju Africa within 8 weeks with 30+ change makers from all over the world to build an AI solution.

Achievements
1. Worked on the loan capacity prediction for the MSMEs given their different features. 
2. Successfully performed preprocessing and analysis on the data. 
3. Implemented models to predict minimum and the maximum loan amount, and the likelihood of loan default. 
4. Deployed the models on a dashboard.Project name: Facilitating access to financial services for underserved populations in Africa I collaborated in the Omdena AI with the impact startup Toju Africa within 8 weeks with 30+ change makers from all over the world to build an AI solution. Achievements 1. Worked on the loan capacity prediction for the MSMEs given their different features. 2. Successfully performed preprocessing and analysis on the data. 3. Implemented models to predict minimum and the maximum loan amount, and the likelihood of loan default. 4. Deployed the models on a dashboard.

Skills: Predictive Analytics · Big Data · Quantitative Analytics · Data Wrangling · Exploratory Data Analysis · Teamwork · Python (Programming Language) · Machine Learning · Data Analysis · Data Cleaning
 

School: Jomo Kenyatta University of Agriculture and Technology

Course: BSc. Actuarial Science

Grade: Upper Second Class Honours

Activities and societies: Jomo Kenyatta University Actuarial Science Association (JKUASA) 
Ascent 14 Leadership Training ProgramActivities and societies: Jomo Kenyatta University Actuarial Science Association (JKUASA) Ascent 14 Leadership Training Program

Actuarial science is the discipline that applies mathematical, statistical and probabilistic methods and financial theories to assess risk in insurance, finance, and other industries and professions

Project topic: Modeling motor insurance claim experience using generalized linear models