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.