Opportunity brief
TalentLo is hiring for the role of Data Scientist!
Who can turn data into decisions. You'll design experiments, build predictive models, and partner with product, engineering, and leadership to solve high impact business problems — from forecasting demand to personalizing user experiences. This role spans the full lifecycle: problem framing, data exploration, modeling, and communicating results that drive action.
Key Responsibilities
Analysis & Modeling (50%)
- Design, build, and validate statistical and machine learning models (classification, regression, clustering, forecasting, etc.)
- Explore and analyze large, messy datasets to identify patterns and opportunities
- Translate ambiguous business questions into well-defined, testable hypotheses
- Build and evaluate recommendation systems, churn models, pricing models, or similar (per business need)
Experimentation (20%)
- Design and analyze A/B tests and multivariate experiments
- Define success metrics and guardrail metrics for product experiments
- Ensure statistical rigor (power analysis, significance testing, avoiding p-hacking)
Production & Engineering Collaboration (15%)
- Partner with ML/data engineers to deploy models into production pipelines
- Monitor deployed models for drift, degradation, and data quality issues
- Write production-quality, version-controlled, reproducible code
Communication & Strategy (15%)
- Present findings and recommendations to cross-functional stakeholders and leadership
- Build dashboards and self-serve tools for non-technical teams
- Influence product and business strategy with data-backed insight
Required Qualifications
- Master's or PhD in Statistics, Computer Science, Mathematics, Economics, or related quantitative field (or equivalent experience)
- 2–5+ years of professional data science experience
- Strong Python skills (pandas, NumPy, scikit-learn, statsmodels) or equivalent R expertise
- Solid foundation in statistics and probability (hypothesis testing, regression, experimental design)
- Advanced SQL skills; comfort with large-scale data warehouses
- Experience designing and analyzing A/B tests
- Strong written and verbal communication skills — able to explain technical concepts to non-technical audiences
Preferred / Nice-to-Have
- Experience with deep learning frameworks (PyTorch, TensorFlow) for applicable use cases
- Experience with cloud-based ML platforms (SageMaker, Vertex AI, Databricks)
- Experience deploying models into production (APIs, batch pipelines)
- Knowledge of causal inference methods
- Domain expertise in [your industry — fintech, healthtech, e-commerce, etc.]
- Experience with big data tools (Spark, BigQuery, Snowflake)
Tech Stack (customize)
- Languages: Python, SQL
- Tools: Jupyter, dbt, Airflow
- Warehouse: Snowflake / BigQuery / Redshift
- Visualization: Tableau / Looker / Plotly
What Success Looks Like (First 90 Days)
This is a full-time, in-office opportunity based in Pune, Maharashtra, with an annual compensation range of ₹28–30 LPA.