Lead Data Scientist

Responsibilities

• Lead development of time series forecasting models (ARIMA, VAR, state-space models, etc.) for business-critical use cases.
• Apply econometric techniques such as WLS, panel data models, and causal inference methods to solve real-world business problems.
• Design and implement Bayesian models and probabilistic frameworks for uncertainty estimation and decision-making.
• Utilize Markov chains and stochastic processes for modeling sequential or behavioral data.
• Translate business problems into robust analytical frameworks and deliver actionable insights.
• Collaborate with stakeholders across business and technical teams to ensure model relevance and impact.
• Mentor junior team members and drive best practices in statistical modeling and experimentation.

• Bachelor's/Master's in Engineering 8+
• 8+ years of experience in Data Science
• Deep expertise in econometric modeling, time series analysis, and causal inference
• Proficiency with large-scale data environments (e.g., Databricks)