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.