About the role
We're hiring a mid-level Product Analyst who goes beyond conventional RCAs and reporting.
This role is split between statistical modelling and simulations and core product analytics, with direct influence on backend product and operational design.
You will work on applied modelling problems that shape how our product and operations function at scale before solutions are built by engineering.
The candidate will have responsibilities across the following functions:
Modelling, Simulations and POCs:
- Build statistical models, simulations, and what-if frameworks to evaluate backend product and ops changes.
- Model real-world scenarios such as:
- Impact of replenishment frequency changes on out-of-stock rates.
- ETA logic tweaks to improve SLA adherence.
- Manpower and capacity planning for dark stores/fulfillment centers.
- Translate ambiguous business questions into structured models with clear assumptions, constraints, and outputs.
- Validate ideas through POCs and simulations before PMs take them to engineering.
Core Product Analytics:
- Own deep RCAs, metric diagnostics, and insight generation for product and operational performance.
- Design decision matrices, trade-off analyses, and dashboards that support fast, real-time decisions.
- Monitor key KPIs, identify anomalies, and recommend corrective actions with clear impact sizing.
- Partner closely with Product, Ops, Business, and Engineering to drive data-backed decisions.
Requirements:
- 3+ years of experience in product analytics, data analytics, or applied analytics roles.
- Strong hands-on skills in Python, SQL, and statistics.
- Experience applying statistical reasoning to real operational or product problems.
- Ability to balance modelling depth with execution speed.
- Clear communicator who can explain assumptions, trade-offs, and results to non- technical stakeholders.
Nice to have:
- Exposure to forecasting, experimentation, or optimisation problems.
- Familiarity with data science fundamentals and model evaluation.
- Experience working in high-scale, operations-heavy products (quick commerce, e-commerce, logistics, supply chain).