About Rafeeq

Rafeeq is a fast-growing on-demand delivery platform operating across food delivery and taxi services. We're building intelligent systems to connect customers, restaurants, and couriers in real-time. Our success depends on making data-driven decisions across product, operations, and ML initiatives.

The Role

We're looking for a Senior Product Analyst to be the analytical backbone of our ML and product teams. You will be the only analyst supporting the entire team initially, which means you'll have broad impact and ownership across multiple problem areas.

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This is a high-leverage role where you'll:

— Define metrics and build dashboards for all our ML systems (ETA, dispatch, surge, incentives)

— Design and analyze experiments to measure feature impact

— Provide data-driven insights to guide product and ML strategy

— Work closely with the ML Team Lead, ML engineers, and Product team

What You'll Do

Metrics & Measurement

— Define Success Metrics: Establish KPIs for ETA accuracy, dispatch efficiency, surge pricing effectiveness, courier incentives, and overall marketplace health

— Build Dashboards: Create real-time monitoring dashboards in our BI tool Looker for key business and ML metrics

— Model Performance: Track ML model performance - accuracy, latency, prediction errors, and business impact

— Marketplace Health: Monitor supply-demand balance, courier utilization, customer wait times, and order cancellation rates

Experimentation & Analysis

— A/B Testing Framework: Design and own the experimentation framework for testing new ML models and product features

— Experiment Analysis: Analyze A/B test results, determine statistical significance, and provide clear recommendations

— Causal Inference: Go beyond correlation to understand causality and treatment effects

— Deep Dives: Conduct ad-hoc analyses to investigate anomalies, understand user behavior, and identify opportunities

Strategic Insights

— Problem Identification: Use data to identify top opportunities for improvement across ETA, dispatch, pricing, and incentives

— Business Reviews: Prepare weekly/monthly reports on key metrics and trends for leadership

— Data Storytelling: Translate complex analyses into clear, actionable insights for technical and non-technical stakeholders

— Roadmap Input: Use data to inform and prioritize product and ML roadmap decisions

Data Infrastructure

— Data Quality: Ensure logging, tracking, and data pipelines are accurate and reliable

— SQL & ETL: Write complex SQL queries to extract, transform, and analyze data from our data warehouse – BigQuery

— Collaboration: Work with Data Engineering to build data marts and improve data infrastructure

— Documentation: Maintain clear documentation of metrics definitions, data models, and analytical methods

What We're Looking For

Required:

— 5+ years of experience as a Product Analyst, Data Analyst, or Data Scientist in a tech company

— Expert SQL skills: You can write complex queries with joins, window functions, CTEs, and optimize for performance

— Statistical rigor: Deep understanding of A/B testing, hypothesis testing, regression analysis, and experimental design

— Data visualization: Proficiency with BI tools (Tableau, Looker, Metabase, Mode, or similar) to build dashboards

— Python: Comfortable with data analysis libraries (Pandas, NumPy, Matplotlib)

— Business acumen: Ability to connect data insights to business impact and strategic decisions

— Communication: Excellent written and verbal communication skills - you can explain complex analysis simply

— Bachelor's or Master's degree in a quantitative field (Statistics, Economics, Mathematics, Computer Science, or related)

Strongly Preferred:

— Experience in marketplace companies (food delivery, ride-hailing, e-commerce, on-demand services)

— Geospatial analysis experience (working with location data, zones, distance calculations)

— Familiarity with ML concepts and working closely with ML/Data Science teams

— Experience with real-time analytics and monitoring production systems

— Background in operations research or supply chain analytics

— Experience with event tracking systems (Amplitude, Mixpanel, Segment)

— Knowledge of causal inference methods (difference-in-differences, propensity scoring, instrumental variables)

Nice to Have:

— Experience analyzing dynamic pricing, surge pricing, or incentive systems

— Knowledge of logistics, routing, or dispatch optimization

— Familiarity with time-series forecasting and demand prediction

— Experience with cloud platforms (AWS, GCP) and data warehouses BigQuery

— Contributions to analytics communities or publications

Why Join Rafeeq?

— Broad Impact: You'll be the analytical foundation for all product and ML decisions - rare opportunity for such wide ownership

— Work with ML Team: Collaborate directly with experienced ML engineers and Team Lead on cutting-edge problems

— Strategic Role: Your insights will directly shape product strategy and ML roadmap - you're not just reporting numbers

— International & Remote: Work from anywhere, remote-first culture, competitive salary in USD/EUR—

— Fast-Paced: See immediate impact of your work, short iteration cycles, quick decision-making

— Competitive Compensation: Market-rate salary in foreign currency + equity

— Growth Opportunity: Potential to build and lead an analytics team as we scale

Problem Areas You'll Support

Food Delivery: ETA prediction accuracy, dispatch optimization, surge pricing, demand forecasting

Taxi (Future): Demand prediction, incentive effectiveness, surge pricing, courier positioning

Platform-Wide: User behavior, conversion funnels, retention, operational efficiency, marketplace balance

Hiring Process

— Application Review: HR team screens applications - quick initial response

— Team Interview: Discussion with ML Team Lead and Product team about analytical approach and experience

— Case Study (Optional): May include a take-home analysis exercise or live problem-solving session

— Final Interview: Conversation covering technical skills, collaboration style, and strategic thinking

— Offer: Fast turnaround, typically 2-3 weeks from application to offer

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We move quickly for strong candidates - international talent welcome!

What Success Looks Like - First 90 Days

— Understand the Business: Deep knowledge of our platform, metrics, data infrastructure, and top priorities

— Build Core Dashboards: Ship 3-5 critical dashboards for marketplace health, ML models, and business metrics

— Launch Experiments: Design and analyze at least 2 A/B tests for new features or ML models

— Deliver Insights: Identify and present top 3-5 opportunities for improvement based on data analysis

— Establish Rhythm: Set up weekly metrics reviews and reporting cadence with the team

— Build Relationships: Strong collaboration with ML engineers, Product team, and Engineering

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Ready to be the analytical brain behind our marketplace platform? We'd love to hear from you.