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inDrive is seeking a Senior Data Analyst to own the Forecasting product, a core system that transforms large-scale marketplace data into daily and monthly forecasts of supply, demand, and financial metrics. These forecasts drive target setting, financial planning, and scenario analysis across the organization.
You will take over a production solution built in Python and BigQuery, ensuring its reliability and credibility while partnering closely with business and finance teams. The role balances technical rigor with business acumen: you'll maintain and improve forecasting models, but the core responsibility is understanding how the business works—how pricing, incentives, marketing, and market events move metrics—and translating that into forecasts that decision-makers can trust.
**Business & Planning Responsibilities:**
- Own the forecast as a decision-making product: track plan vs. actual, decompose variances into business drivers (seasonality, pricing, incentives, marketing, external events), and explain changes in business terms
- Support company planning cycles by providing forecast baselines for target setting and budgeting; align assumptions with finance and business stakeholders
- Build and run scenario ("what-if") analysis for planned interventions: pricing changes, incentive and marketing spend, product launches, market expansion
- Maintain dependency logic connecting supply, demand, and financial metrics to ensure forecasts remain mutually consistent and aggregate correctly across markets
- Translate ambiguous business questions into measurable forecasting problems; communicate assumptions, uncertainty, and limitations clearly to both business and technical audiences
**Forecast Production Responsibilities:**
- Run and monitor recurring daily and monthly forecasts: validate data completeness, perform sanity checks, track run-over-run drift
- Investigate anomalies end-to-end—from inputs and business transformations to forecast outputs—identifying root business causes, not just technical fixes
- Improve models pragmatically: establish baselines, perform honest validation, and make model choices driven by measurable planning value rather than sophistication
- Keep the solution maintainable: write readable Python, maintain documentation, version changes appropriately
**Technology Environment:**
Python (pandas, NumPy, scikit-learn, Prophet), BigQuery, Databricks, Git, and GitHub Actions. This is an analyst role in an engineering-friendly environment; you should be comfortable in this stack, though deep ML engineering is not the core focus.
**Requirements:**
- 4+ years in analytics, forecasting, or planning roles (e.g., marketplace or product analytics, demand planning, decision science)
- Strong understanding of business planning: plan/fact cycles, target setting, driver-based models, unit economics; ability to see business metrics as a connected system rather than isolated time series
- Practical command of time-series forecasting: seasonality, holidays, external regressors, structural breaks, missing data; able to own and improve production models
- Confident Python (pandas ecosystem): able to maintain and extend existing production codebases
- Advanced SQL and experience with large datasets in cloud data warehouses
- Rigorous validation habits: appropriate baselines, no data leakage, error metrics tied to business impact
- Ownership mindset: comfortable investigating issues across data, model, and integration boundaries
- Professional working proficiency in English and ability to defend numbers in front of senior stakeholders
**Nice to Have:**
- Background in mobility, marketplaces, or other supply-and-demand systems
- Experience supporting financial planning, S&OP, or budgeting processes
- Econometrics and causal inference; marketing-response models (adstock, saturation, investment payback)
- Hierarchical forecasting across multiple markets
- Experience owning or supporting production batch pipelines; BigQuery, Git-based workflows, CI/CD
