Role Overview
We are looking for a Lead Data Scientist who is highly hands-on, technically strong, and capable of leading a small team while owning end-to-end delivery of data science solutions. This role requires a balance of deep individual contribution (7080%) and team leadership & stakeholder management (2030%).
Key Responsibilities
- Design, develop, and deploy end-to-end data science solutions from problem framing to production
- Work hands-on with SQL and Python for data extraction, analysis, feature engineering, and modeling
- Build and optimize machine learning models using classical ML techniques
- Apply advanced analytical methods such as:
- Causal inference
- Price elasticity modeling
- Forecasting / time series analysis
- Optimization techniques
- Translating business problems into data science approaches and measurable outcomes
- Lead, mentor, and review work of junior and mid-level data scientists
- Ensure high-quality, scalable, and maintainable model delivery
- Collaborate closely with product, engineering, and business stakeholders
- Drive best practices in modeling, experimentation, and code quality
Required Skills & Qualifications
- 811 years of experience in Data Science / Machine Learning
- Strong hands-on expertise in SQL (complex queries, performance tuning)
- Advanced proficiency in Python (pandas, numpy, scikit-learn, statsmodels, etc.)
- Solid understanding of statistics and machine learning fundamentals
- Proven experience in one or more of the following:
- Causal modeling / experimentation
- Price elasticity / pricing models
- Forecasting / time-series models
- Optimization or classical ML algorithms
- Experience leading a team and owning delivery commitments
- Strong problem-solving and communication skills
Good to Have
- Experience deploying models into production environments
- Familiarity with cloud platforms or MLOps workflows
- Prior experience working with business stakeholders in retail, pricing, supply chain, or growth analytics
