Data Scientist

Job Description Role Summary : We are seeking an experienced Data Scientist to drive data-driven decision-making for our bids, operations, and financial modeling functions. You will leverage advanced analytics and predictive modeling to help Ceres management optimize bid pricing, operational productivity, and margin forecasting by analyzing large volumes of historical and operational data. This is a hands-on, high-impact role interfacing with global stakeholders, particularly in pricing strategy, operational forecasting, and business performance analytics. - Bid Win Model : Develop predictive models estimating win probability by client, region, scope, and competitor profile. - Pricing Engine : Build elasticity-based pricing guidance to support competitive bid decisions. - Operations Forecasting : Model production rates by debris type, weather, crew mix, and logistics routes. - Margin Forecast : Create financial simulation models to assess cost drivers (fuel, disposal, distance, etc.) and scenario outcomes. - MLOps Foundation : Implement automated retraining, monitoring, and governance frameworks for deployed models. Core Responsibilities : - Design and develop data models, pipelines, and predictive systems using Python and SQL across multiple data sources Salesforce, ERP (NetSuite/Vista/ERPLY), GIS, and weather data. - Conduct feature engineering on operational and geospatial datasets (e.g., buffer zones, competitor features, crew metrics). - Build, validate, and deploy models for : o Classification : Win/loss predictions o Regression : Price and cost forecasts o Time Series : Throughput and demand projections o Optimization : Crew and equipment routing, shift planning - Evaluate models using statistical and business metrics (AUC, RMSE, MAE, uplift). - Deploy models into dashboards or applications (e.g., Power BI, Salesforce, Google Sheets). - Present actionable insights and executive-level narratives to senior management. - Maintain reproducibility and data governance, ensuring version control and auditability. Required Qualifications : - Postgraduate degree in Data Science, Statistics, Applied Mathematics, Engineering, Operations Research, or related fields (IITs, NITs, IIITs, ISI, or Tier-1 Universities preferred). - 610+ years of experience in applied data science within pricing, demand forecasting, operations, or financial modeling. - Proficiency in Python (pandas, scikit-learn, statsmodels, XGBoost/LightGBM) and SQL. - Hands-on experience in building data pipelines (Airflow, DBT) and working with structured/unstructured data. - Exposure to geospatial analytics (GeoPandas, ArcGIS, QGIS), weather data, or location intelligence. - Understanding of A/B testing, causal inference, and statistical experiment design. - Familiarity with MLOps frameworks for versioning, monitoring, and automated retraining. - Excellent communication skills to translate analytical insights into business impact. Preferred Experience : - Prior work in construction, infrastructure, logistics, utilities, or disaster management sectors. - Experience integrating financial modeling with operations and pricing analytics. - Experience working with U.S. clients or in global delivery centers supporting analytics for large enterprises. - Understanding of supply chain, equipment utilization, and manpower productivity analytics. Why Join Ceres Environmental - Be part of a purpose-driven company that helps communities recover from natural disasters worldwide. - Work in a data-first culture where analytics directly influence pricing, operations, and profitability. - Collaborate with U.S. leadership on strategic bids and cost-optimization projects. - Enjoy the stability of a global enterprise with the agility of a startup-style GCC in India.