Forecasting Data Scientist

Artech L.L.C.; Bengaluru; On-site; INR 3,000,000 - 5,000,000; Full time

Job summary

Artech L.L.C. is seeking an experienced Demand Forecasting Data Scientist in Bengaluru, India, for a full-time role. The candidate should excel in time series forecasting, machine learning, and supply chain analytics, with hands-on Databricks and Python experience.

Responsibilities include designing forecasting models, building end-to-end pipelines on Databricks, and applying ARIMA/SARIMA, Prophet, XGBoost, and DL approaches. Strong MLOps and CI/CD exposure is expected.

Qualifications

• 6+ years of experience as a Data Scientist focusing on demand forecasting or supply chain analytics.
• Strong hands-on Python experience with NumPy, Pandas, SciPy.
• Experience with time series forecasting techniques and real-world demand planning use cases.
• Hands-on Databricks experience, including Spark, notebooks, and distributed data processing.
• Experience with ML/DL model development and deployment, cloud/big data environments.
• Practical knowledge of MLOps, model monitoring, and CI/CD pipelines.
• Knowledge of Nixtla library is a plus.

Responsibilities

• Design, develop, and deploy demand forecasting models using time series, ML, and DL techniques.
• Build end-to-end forecasting pipelines on Databricks leveraging distributed computing and scalable architectures.
• Apply ARIMA/SARIMA, Prophet, XGBoost, Random Forest, LSTM/GRU, TimeGPT, and hybrid models.
• Evaluate forecast accuracy using metrics like MAPE, wMAPE, and Bias.
• Contribute to coding best practices, model governance, documentation, and MLOps workflows.

Skills

Time Series Forecasting

Demand Forecasting

Supply Chain Analytics

Python

Databricks

Spark

ML/DL

ARIMA/SARIMA

Prophet

XGBoost

LSTM/GRU

MLOps

CI/CD

Nixtla

Tools

Databricks

Spark

Nixtla

Job description

Job Title: Demand Forecasting Data Scientist

Experience: 6+ years

Location: BENGALURU, India (Full time)

Job Summary

We are seeking an experienced Demand Forecasting Data Scientist with strong expertise in time series forecasting, machine learning, and supply chain analytics. The ideal candidate will have hands-on experience working with Databricks and Python

Key Responsibilities

• Design, develop, and deploy demand forecasting models using time series, machine learning, and deep learning techniques.
• Build end-to-end forecasting pipelines on Databricks leveraging distributed computing and scalable architectures.
• Apply statistical and ML techniques such as ARIMA/SARIMA, Prophet, XGBoost, Random Forest, LSTM, GRU, TimeGPT and hybrid models.
• Evaluate and improve forecast accuracy using appropriate metrics (MAPE, wMAPE, Bias).
• Contribute to best practices in coding, model governance, documentation, and MLOps workflows.

Required Skills & Qualifications

Technical Skills

• 6 years of experience as a Data Scientist with a strong focus on demand forecasting or supply chain analytics.
• Strong hands-on experience with Python and its associated libraries:
• NumPy, Pandas, SciPy
• scikit-learn
• statsmodels
• TensorFlow / PyTorch (for DL models)
• Solid experience with Time Series Forecasting techniques and real-world demand planning use cases.
• Hands-on experience with Databricks, including Spark, notebooks, and distributed data processing.
• Practical exposure to Machine Learning and Deep Learning model development and deployment.
• Experience working with large, complex datasets in cloud-based or big data environments.
• Practical understanding of Nixtla library is a plus.
• Experience with MLOps, model monitoring, and CI/CD pipelines.

Domain Knowledge

• Strong Supply Chain domain knowledge, especially demand forecasting, inventory planning, and sales forecasting.
• Understanding of forecast lifecycle, demand variability, and business constraints.