Key Responsibilities

Data Analysis & Insights

Collect, clean, and analyze operational, financial, and customer data to identify trends, patterns, and anomalies.

Produce regular and ad-hoc reports for internal teams (operations, finance, customer experience, engineering) to support data-driven decision making.

Build intuitive dashboards and visualizations that track KPIs according to departments or projects.

Partner with business units to define metrics, validate data, and turn analysis into actionable recommendations.

Support Model Development & Research

Assist the data science team in preparing datasets for machine learning models in areas such as credit scoring, predictive maintenance, route optimization, and driver behavior scoring.

Document data sources, assumptions, and model inputs for transparency and reproducibility.

Data Infrastructure & Quality

Work closely with engineering to ensure data pipelines are reliable, accurate, and scalable.

Validate and reconcile data from multiple systems (e.g., telematics, Jani digital fare collection, billing, CRM, financial systems).

Establish basic data quality checks and flag anomalies proactively.

Stakeholder Engagement

Act as a bridge between technical and non-technical teams, translating data findings into clear, actionable insights.

Support training sessions and workshops to build data literacy across the organization.

Qualifications

Bachelor’s degree in Data Science, Statistics, Computer Science, Economics, Mathematics, or a related quantitative field.

2–4 years of professional experience in data analysis or business intelligence.

Proficiency in SQL for data extraction and transformation.

Strong skills in Python (Pandas, NumPy, matplotlib/Seaborn/Plotly) or R for analysis and visualization.

Experience with BI/dashboarding tools (e.g., AWS QuickSight, Power BI, Tableau, Looker).

Solid understanding of data cleaning, statistical analysis, and basic machine learning concepts.

Familiarity with cloud platforms (AWS preferred) is an advantage.

Excellent communication skills with the ability to explain data insights to non-technical audiences.

Knowledge of the Kenyan public transport sector or fintech/mobility data is a plus.