Senior Data Scientist

Key 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.

• Work with large datasets using Databricks

• 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.

Responsibilities
Must-Have Qualifications

• Strong foundation in econometrics and time series analysis (this is critical for the role).

• Hands-on experience with:

• Time series models (ARIMA, SARIMA, VAR, forecasting techniques)

• Econometric methods (WLS, regression diagnostics, panel data models)

• Causal inference (A/B testing, quasi-experimental methods)

• Bayesian statistics and probabilistic modeling

• Markov chains or stochastic modeling

• Proficiency in Python along with SQL.

• Experience working with Databricks or similar big data platforms.

• Ability to clearly communicate complex statistical concepts to non-technical stakeholders.

Qualifications
Secondary / Good-to-Have Skills (General Data Science)

• Experience with machine learning models (classification, regression, tree-based models, etc.)

• Familiarity with feature engineering, model validation, and performance tuning

• Exposure to ML pipelines and MLOps concepts