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inDrive is seeking a Senior Data Analyst to own the Forecasting product, a critical 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 inherit a working production solution built in Python and BigQuery, and your core responsibility is ensuring its reliability and business value. This is not a modeling role for its own sake—it is about deeply understanding how the business operates: how pricing, incentives, marketing, and market events move metrics, how those metrics interconnect, and what decision-makers need to plan with confidence.
Key responsibilities include:
**Business & Planning:**
- 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, and aligning 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:**
- 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 the business reason, not just technical fixes
- Improve models pragmatically using baselines, honest validation, and model choices driven by measurable planning value rather than sophistication
- Keep the solution maintainable: write readable Python, maintain documentation, version changes
**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 of the job.
**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, not 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 a cloud data warehouse
- 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
