Data Scientist Forecasting & Predictive Analytics

Experience: 3-8 Years
Location: Bangalore (Client Location)

Job Description

1. 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.

2. 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.

3. 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.

4. 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.

5. 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.

6. 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

- 38 years of experience in Data Science or Machine Learning.
- Solid 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.
- Robust 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.r excellence.

📌 Data Scientist (Bengaluru)
🏢 Celebal Technologies
📍 Bengaluru