Sr Data Scientist

Job SummaryThe Senior Data Scientist designs and deploys statistical, forecasting, and machine learning solutions to solve complex business problems. This role works with cross-functional teams to build production-ready models, generate actionable insights, and improve planning and decision-making at scale.The role requires strong expertise in statistics, time series analysis, probabilistic forecasting, machine learning, and Google Cloud Platform (GCP). ResponsibilitiesStatistical Modeling & ForecastingBuild and deploy statistical and probabilistic forecasting models for demand, capacity, and trend analysisApply time series methods including regression-based models, ARIMA/SARIMA, and state-space modelsDefine modeling assumptions, forecast uncertainty, and evaluation methods

Machine Learning & Predictive ModelingBuild and deploy machine learning models for forecasting and prediction, including regression, tree-based models, gradient boosting and neural networksSelect statistical or ML approaches based on accuracy, interpretability, robustness, and operational needsDevelop features and run experiments to improve model performance

MLOps & Production DeploymentOwn the model lifecycle, including development, backtesting, deployment, monitoring, and retrainingImplement model monitoring, performance tracking, and data drift detectionEnsure models are versioned, reproducible, and production-ready

Data Engineering & ModelingPerform exploratory data analysis, feature engineering, and hypothesis testing on large, complex datasetsIdentify data requirements for forecasting and predictive modeling, including key inputs, data gaps, and quality needsWork with big data technologies and distributed data processing to support scalable modelingPartner with data engineering teams to ensure data quality, availability, and efficient data pipelines

Visualization & InsightsCreate visualizations to communicate forecasts, trends, and model outputsTranslate model results into actionable insights for business and operational stakeholders

Collaboration & Stakeholder EngagementWork closely with product managers, engineers, and business teams to define forecasting and analytics requirementsCommunicate modeling approaches, assumptions, and results clearly to technical and non-technical stakeholders

Qualifications4+ years of experience in data science, applied statistics, or machine learningStrong foundation in statistics and experience applying statistical methods in productionProven experience with time series analysis and probabilistic forecastingHands-on experience with machine learning models such as regression, boosting, and neural networksExperience owning production data science models, including deployment and monitoringExperience working with large datasets and using SQL and Python for analytical and modeling workflowsProficiency in Python and common DS/ML libraries (e.g., pandas, NumPy, scikit-learn, statsmodels, PyTorch/TensorFlow)Experience working on Google Cloud Platform (GCP)Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field