Description
model evaluation
feature engineering
forecasting models
pricing engine
mlops
dashboard deployment
You’ll work in a dynamic, data-driven environment, collaborating with U.S. stakeholders on real-world analytics problems that shape pricing and operations strategy. Expect exposure to large-scale operational data, rapid prototyping of models, and opportunities to own analytics products end-to-end from concept to deployment.
This is a hands-on, high-impact role interfacing with global stakeholders, particularly in pricing strategy, operational forecasting, and business performance analytics.
You will leverage advanced analytics and predictive modelling to help Ceres management optimize bid pricing, operational productivity, and margin forecasting by analysing large volumes of historical and operational data.
- Evaluate models using AUC, RMSE, MAE, and uplift metrics.
- Conduct feature engineering on operational and geospatial datasets.
- Operations Forecasting: Model production rates by debris type, weather, crew mix, and logistics routes.
- Pricing Engine: Build elasticity-based pricing guidance to support competitive bid decisions.
- Margin Forecast: Create financial simulation models to assess cost drivers and scenario outcomes.
- Bid Win Model: Develop predictive models estimating win probability by client, region, scope, and competitor profile.
- Deploy models into dashboards or applications (Power BI, Salesforce, Google Sheets).
- Design and develop data models, pipelines, and predictive systems using Python and SQL across multiple data sources (Salesforce, ERP, GIS, and weather data).
- Build, validate, and deploy models for:
- Maintain reproducibility and governance through version control and auditability.
- MLOps Foundation: Implement automated retraining, monitoring, and governance frameworks for deployed models.
Requirements
python
sql
airflow
dbt
geopandas
postgraduate
We are seeking an experienced Data Scientist to drive data-driven decision-making for our bids, operations, and financial modelling functions.
- Exposure to geospatial analytics (GeoPandas, ArcGIS, QGIS) and weather data.
- 7–12 years of applied data science experience in pricing, forecasting, or financial modelling.
- Hands-on experience building data pipelines (Airflow, DBT).
- Excellent communication and storytelling skills.
- Understanding of A/B testing, causal inference, and experiment design.
- Familiarity with MLOps frameworks for model versioning and monitoring.
- Present actionable insights and executive narratives to senior management.
- Proficiency in Python (pandas, scikit-learn, stats models, XGBoost/LightGBM) and SQL.
- Postgraduate degree in Data Science, Statistics, Applied Mathematics, Engineering, Operations Research, or related fields (IITs, NITs, IIITs, ISI, or Tier-1 universities preferred).
Benefits
At Ceres India, you’re more than just an employee your part of a mission-driven team helping communities recover and rebuild after disasters. We value initiative, diversity, and ownership. You’ll find opportunities for growth, travel, and impact in a culture that thrives on teamwork and resilience.
- The chance to make a lasting difference for communities worldwide.
- Opportunities for professional growth and advancement.
Training + Development
Information not given or found
