Senior Product Analyst - Growth & Retention at M-KOPA

What You'll Do

• At M-KOPA, you'll own our growth measurement framework – defining key events, conversion funnels, customer cohorts, and success metrics across mobile app, CRM systems, and telesales channels.

Key responsibilities include:

• Building our Looker analytics layer: Collaborate with analytics engineers to create reusable LookML data models, set up governed metrics, automated data tables, user permissions, and use Git for version control
• Moving from spreadsheets to a single source of truth: Audit Excel files, recreate them as data models using dbt, and replace manual tracking with automated Looker dashboards
• Leading the transition to data-driven tools: Help teams migrate from manual spreadsheet tracking to automated dashboards, including migrating funnel data input into structured systems
• Building automated dashboards: Create dashboards for upgrade conversion rates, repeat purchase behaviour, customer lifetime value (LTV), and unit economics
• Designing agent performance and incentive analytics: Build dashboards tracking call volume, conversion rates, talk time efficiency, lead quality, and revenue per agent. Design data-driven incentive structures and real-time leaderboards
• Calculating and tracking customer lifetime value: Build models estimating profit per customer cohort and track early signals predicting long-term value

Your Analytics Environment

Tools & Technologies:

• Data transformation: dbt, SQL
• Visualization: Looker, LookML
• Product analytics: Amplitude, Mixpanel, Statsig
• CRM & engagement: Braze, CleverTap, Fresh Desk
• Analysis: Python or R
• Data pipeline: Fivetran, Stitch, Airbyte
• Version control: Git

Required Experience:

• Proven track record in product analytics at fintech, telco, e-commerce, or subscription company
• Strong SQL skills and experience with dbt for building reliable data models
• Hands-on experience with Looker (dashboards, LookML, data governance and permissions)
• Python or R for analysing experiments, building cohort models, and calculating customer lifetime value
• Experience combining data from multiple sources (Amplitude, Mixpanel, Statsig, Braze, CleverTap, call-center data)
• Understanding of experiment design and analysis
• Experience designing performance metrics and incentive structures