Lead Data Scientist / Manager - Data Science (Forecasting)

Role Summary :

We are seeking an experienced Lead Data Scientist / Manager - Data Science with strong expertise in forecasting, predictive analytics, machine learning, and statistical modeling.

The ideal candidate will lead the design and deployment of forecasting solutions that drive strategic business decisions across areas such as revenue planning, demand forecasting, workforce planning, supply chain optimization, and customer analytics.

This position requires a blend of technical excellence, business acumen, stakeholder management, and team leadership.

Key Responsibilities :

Forecasting & Predictive Analytics :

- Build and deploy forecasting models for business metrics such as sales, demand, revenue, customer growth, inventory, and workforce planning.

- Develop time series forecasting models using techniques such as ARIMA/SARIMA, Prophet, Exponential Smoothing, XGBoost, Random Forest, and Deep Learning models (LSTM, Transformer-based forecasting).

- Evaluate forecast accuracy and continuously improve model performance.

- Conduct scenario analysis and what-if simulations to support business planning.

Data Science Leadership :

- Lead a team of data scientists, analysts, and ML engineers.

- Mentor and coach team members on advanced analytics and machine learning techniques.

- Define project roadmaps, priorities, and delivery timelines.

- Establish best practices for model development, validation, and deployment.

Stakeholder Management :

- Collaborate with business leaders to understand forecasting requirements.

- Translate business problems into analytical solutions.

- Present insights, recommendations, and forecasts to senior leadership.

- Drive adoption of data-driven decision-making across the organization.

Machine Learning & Model Development :

- Design end-to-end ML solutions from data preparation to production deployment.

- Develop predictive and prescriptive analytics solutions.

- Monitor model performance and ensure model governance standards are followed.

- Work with engineering teams to productionize models.

Data Engineering & Analytics :

- Work with large-scale structured and unstructured datasets.

- Build feature engineering pipelines and data quality frameworks.

- Ensure scalable and efficient data processing using cloud platforms and distributed computing frameworks.

Required Qualifications :

- BE/BTech / MSc Statistics / PhD

Experience :

- 8 - 12+ years of overall analytics/data science experience.

- 3 - 5+ years leading data science teams.

- Strong hands-on experience in forecasting and predictive modeling.

- Experience delivering forecasting solutions in production environments.

Technical Skills :

- Programming : Python, SQL, R (preferred)

- Forecasting & Statistics : Time Series Analysis, Forecast Accuracy Metrics (MAPE, RMSE, WAPE), Statistical Modeling, Econometrics, Experimental Design

- Machine Learning : Scikit-learn, XGBoost, LightGBM, TensorFlow/PyTorch

- Cloud Platforms : Azure, AWS, GCP

- Data Technologies : Databricks, Spark, Snowflake, Hadoop (preferred)

Preferred Industry Experience :

- Retail, FMCG, E-commerce, Manufacturing, Supply Chain, Banking & Financial Services, Technology

Leadership Competencies :

- Team Leadership, Strategic Thinking, Stakeholder Management, Executive Communication, Problem Solving, Project Management, Cross-functional Collaboration