Data Scientist – Operations

About Ceres India

Ceres India (Ceres Environmental India Pvt. Ltd.) serves as the Global Capabilities Centre for
Ceres Global
, embodying strategic value, innovation, and operational excellence. With a highly skilled and diverse team, Ceres India drives efficiency and delivers exceptional support services across global operations

Driven by Purpose, Powered by People

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.

What We Are Looking For

We are seeking an experienced
Data Scientist
to drive data-driven decision-making for our bids, operations, and financial modelling functions.

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.

This is a
hands-on, high-impact role
interfacing with global stakeholders, particularly in
pricing strategy, operational forecasting, and business performance analytics
.

Key Analytical Focus Areas:

• 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 and scenario outcomes.
• MLOps Foundation:
  Implement automated retraining, monitoring, and governance frameworks for deployed models.

What You Will Do

• Design and develop
  data models, pipelines, and predictive systems
  using Python and SQL across multiple data sources (Salesforce, ERP, GIS, and weather data).
• Conduct
  feature engineering
  on operational and geospatial datasets.
• Build, validate, and deploy models for:
• Classification (Win/Loss predictions)
• Regression (Price and cost forecasts)
• Time Series (Throughput and demand projections)
• Optimization (Crew and equipment routing, shift planning)
• Evaluate models using
  AUC, RMSE, MAE, and uplift
  metrics.
• Deploy models into dashboards or applications (Power BI, Salesforce, Google Sheets).
• Present
  actionable insights
  and executive narratives to senior management.
• Maintain
  reproducibility and governance
  through 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).
• 7–12 years
  of applied data science experience in pricing, forecasting, or financial modelling.
• Proficiency in
  Python
  (pandas, scikit-learn, stats models, XGBoost/LightGBM) and
  SQL
  .
• Hands-on experience building
  data pipelines
  (Airflow, DBT).
• Exposure to
  geospatial analytics
  (GeoPandas, ArcGIS, QGIS) and weather data.
• Understanding of
  A/B testing
  , causal inference, and experiment design.
• Familiarity with
  MLOps
  frameworks for model versioning and monitoring.
• Excellent communication and storytelling skills.

What to Expect

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.

Why Join Ceres India?

At Ceres India, you won't just have a job —
you'll have a mission.

Your work directly impacts the speed and strength of community recovery after disasters.

We offer:

• A
  collaborative, mission-driven culture
  .
• Opportunities for professional growth and advancement.
• The
  chance to make a lasting difference
  for communities worldwide.