Data Scientist at Celebal Technologies in Bengaluru

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.
• 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.r excellence.