Senior Data Scientist

Data Science-Gen AI EngineerLead 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.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 modelingMarkov chains or stochastic modelingProficiency 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.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.Adapting To ChangeAttention To ConsistencyBig Data OptimizationCloud Security ManagementData Backup and RecoveryData StrategyInterpersonal Dynamics with CoworkersResults OrientationStakeholder EngagementTime Management SkillsWorking under PressureWriting Communication Skills