inDrive

Senior Data Analyst

inDrive Almaty, Kazakhstan

IT Services and IT Consulting · 1,001-5,000 employees

Aug 26
data-analyst Mid (2-5 yrs) Full-time Kazakhstan
Log in to apply, save this posting, or score it against your profile with AI.

About the role

You will own the forecasting product by tracking plan versus actual metrics and decomposing variances into business drivers. Additionally, you will support company planning cycles and build scenario analysis to guide decision-making for business stakeholders.

What they look for

Python BigQuery SQL Data analysis Forecasting Marketplace analytics Financial planning Scenario analysis Pandas NumPy Scikit-learn Prophet Databricks Git GitHub Actions Unit economics

Requirements

Candidates must have 4+ years of experience in analytics, forecasting, or planning roles with a strong command of Python and SQL. You should possess a deep understanding of business planning cycles and the ability to communicate complex data insights to senior stakeholders.

Benefits

Mentoring Career consulting Learning programs Global Talent Exchange Program Sports activities Volunteering projects Language courses Speaking clubs

Full description

Senior Data Analyst

Department: Analytics Department

Employment Type: Full Time

Location: Kazakhstan

Description

inDrive's Forecasting product turns large-scale marketplace data into daily and monthly forecasts of the company's core supply, demand and financial metrics. These forecasts are the backbone of target setting, financial planning and scenario analysis for business teams and leadership.

We are looking for a Senior Analyst to own this product: the quality and credibility of the numbers, the planning processes they feed, and the story behind every deviation. You will take over a working production solution (Python, BigQuery) and keep it reliably serving the business — but the core of the role is not modeling for its own sake. It is understanding how the business works: how pricing, incentives, marketing and market events move metrics, how those metrics connect to each other, and what decision-makers need from a forecast to plan with confidence.

Key Responsibilities

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 in business terms why the numbers changed
  • Support company planning cycles: provide forecast baselines for target setting and budgeting, and 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 the dependency logic connecting supply, demand and financial metrics, so that forecasts stay 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: data completeness, sanity checks, run-over-run drift
  • Investigate anomalies end to end — from inputs and business transformations to forecast outputs — getting to the business reason, not just a technical fix
  • Improve models pragmatically: baselines, honest validation, and model choices driven by measurable planning value rather than sophistication.
  • Keep the solution maintainable: readable Python, documentation, versioned changes

Skills, Knowledge and Expertise

  • 4+ years in analytics, forecasting or planning roles — for example marketplace or product analytics, demand planning, or decision science
  • Strong understanding of how a business is planned: plan/fact cycles, target setting, driver-based models, unit economics. You see business metrics as a connected system, not as isolated time series
  • Practical command of time-series forecasting — seasonality, holidays, external regressors, structural breaks, missing data — enough to own and improve production models
  • Confident Python (pandas ecosystem): able to maintain and extend an existing production codebase
  • 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 the ability to defend a number 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

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 at home in this stack, but deep ML engineering is not the core of the job.

Why join us

  • Help us challenge injustice by creating fair choices for millions of people across 48 countries
  • Develop your professional skills with access to mentoring, career consulting, and learning programs
  • Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program
  • Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects
  • Work alongside people who take initiative, speak openly, and challenge themselves to grow
  • Improve your language skills through co-financed courses and internal speaking clubs

Final benefits may vary depending on the location.

Similar roles