Data Scientist - Forecasting & Predictive Analytics
First seen by Alion on Aug 6, 2026.
Data Scientist - Forecasting & Predictive Analytics
Experience : 3- 8 Years
Location : Bangalore (Client Location)
Job Description :
Forecasting & Predictive Analytics :
- Develop accurate demand forecasting models using historical sales, seasonal trends, promotions, and external factors.
- Build and optimize time series forecasting models for business planning and inventory optimization.
- Design and implement customer churn prediction models to identify at-risk customers and improve retention strategies.
- Develop price optimization and price elasticity models to maximize revenue and profitability.
- Analyze customer behavior, product demand, and business trends to generate actionable insights.
Model Development :
- Build, validate, and deploy machine learning models for forecasting, customer analytics, and pricing.
- Develop predictive models using statistical and machine learning techniques.
- Perform feature engineering, model evaluation, hyperparameter tuning, and model monitoring.
- Improve model performance through continuous experimentation and optimization.
Time Series Analytics :
- Build forecasting models using techniques such as ARIMA, SARIMA, Prophet, Holt-Winters, and machine learning-based forecasting methods.
- Analyze seasonality, trends, cyclic patterns, and anomalies in time series data.
- Support forecasting use cases across sales, demand planning, supply chain, and business operations.
Data Analysis & Business Insights :
- Perform exploratory data analysis (EDA) to identify trends, patterns, and business opportunities.
- Translate complex business problems into analytical solutions.
- Present insights through dashboards and visualizations to support business decision-making.
Collaboration :
- Work closely with Product, Business, Supply Chain, Marketing, Finance, and Data Engineering teams.
- Collaborate with Data Engineers to ensure data readiness, feature availability, and scalable ML pipelines.
- Partner with stakeholders to understand forecasting requirements and deliver data-driven solutions.
Model Deployment & Monitoring :
- Deploy machine learning models into production environments.
- Monitor model performance and retrain models as required.
- Establish model governance and maintain documentation for reproducibility.
Must-Have Skills :
- 3 - 8 years of experience in Data Science or Machine Learning.
- Strong proficiency in Python (Pandas, NumPy, Scikit-learn, Statsmodels, Prophet).
- Strong SQL skills for querying and analyzing large datasets.
- Hands-on experience with Time Series Forecasting and statistical forecasting techniques.
- Experience in Demand Forecasting for retail, supply chain, or business planning.
- Experience building Customer Churn Prediction models.
- Strong understanding of Price Optimization and Price Elasticity modelling.
- Experience with forecasting models such as ARIMA, SARIMA, Prophet, Holt-Winters, XGBoost, LightGBM, and LSTM.
- Strong understanding of regression, classification, clustering, and model evaluation techniques.
- Experience with BI tools such as Tableau or Power BI.
- Strong statistical knowledge and hypothesis testing.
Good-to-Have Skills :
- Experience with cloud platforms such as Azure or AWS.
- Knowledge of MLOps and model deployment frameworks.
- Experience with Databricks or Spark.
- Familiarity with A/B Testing and experimentation.
- Strong communication and stakeholder management skills.
- Ability to work independently in a fast-paced environment.
- Experience in Retail, E-commerce, FMCG, or Supply Chain analytics is preferred for excellence.
Skills
Data Science, Machine Learning, Python, SQL, Time Series Forecasting, Predictive Analytics, Predictive Modeling, Statistical Modeling, MLOps