Data Scientist (Demand Forecasting)

Role : Data Scientist

Experience : 4 to 7 years

Location : Chennai WFO

Immediate Joiners Preferred

Job Overview

We are seeking an experienced professional with strong expertise in forecasting models to support data-driven decision-making across the organization. The ideal candidate will design, implement, and optimize statistical and machine learning models to predict trends, demand, revenue, or operational metrics based on business needs.

Key Responsibilities

Develop, validate, and deploy time series forecasting models (ARIMA, SARIMA, Prophet, ETS, VAR, etc.) and machine learning-based forecasting techniques (XGBoost, Random Forest, LSTM, Transformer models, etc.).

Collect, clean, and preprocess historical data from multiple sources to build reliable forecasting datasets.

Perform feature engineering, seasonality / trend analysis, anomaly detection, and scenario simulations.

Collaborate with business stakeholders to understand forecasting needs across functions such as sales, supply chain, finance, marketing, or inventory planning.

Continuously monitor model performance, perform backtesting, and implement retraining strategies.

Build automated forecasting pipelines using Python, SQL, and cloud-based tools (AWS / Azure / GCP).

Present insights and recommendations through dashboards or visualizations using Power BI, Tableau, or Python (Matplotlib / Plotly).

Document methodologies and contribute to forecasting best practices and governance frameworks.

Required Skills & Qualifications

Bachelor’s / Master’s degree in Statistics, Data Science, Mathematics, Computer Science, Economics, or related field.

Hands-on experience (4+ years) in building and deploying forecasting or predictive models.

Strong proficiency in Python / R, including libraries such as pandas, statsmodels, scikit-learn, Prophet, or TensorFlow / PyTorch (for deep learning).

Solid understanding of statistical modeling, probability, and time series analysis.

Experience with SQL and data warehousing (Snowflake, Redshift, BigQuery, etc.).

Knowledge of MLOps practices and cloud platforms is an advantage.

Excellent analytical thinking and communication skills.