Senior Data Scientist, Time Series Forecasting

Overview

As a Senior Data Scientist, you will design, deploy and improve analytical, machine learning and forecasting models for demand planning, revenue management, commercial planning and other business problems.

What you'll do

• Own end-to-end discovery, design, configuration, testing and deployment of analytical models and communicate with internal and external stakeholders.
• Identify relevant internal and external data sources.
• Recommend and oversee appropriate statistical, machine learning and predictive modeling concepts.
• Apply machine learning techniques including clustering, regression, ensemble methods, neural networks, time series and optimization.
• Analyze, tune and improve production forecasting systems to enhance forecast accuracy and reliability.
• Diagnose sources of forecast error and identify opportunities for model and parameter improvements while maintaining production stability.
• Understand, explain and defend existing forecasts to customers, including their key drivers, assumptions, methodology and generation process.
• Translate complex forecasting concepts into clear business language and address customer questions or challenges.
• Develop and deploy advanced models for demand planning, forecasting and sensing.
• Design and build models for revenue management and commercial planning.
• Work on market intelligence, heuristic, linear programming and genetic algorithm optimization, anomaly detection, simulation and stochastic models.
• Use advances in AI and machine learning to solve business problems.
• Apply common business metrics and generate new metrics as needed.
• Collaborate with clients, project managers, solution architects, consultants and data engineers to deliver projects.
• Guide junior data scientists and oversee their activities.
• Maintain high coding standards and best practices within the organization.

What you'll need

• 4 to 6 years of experience in Data Science and Analytics.
• A Master’s Degree in Operations Research, Mathematics, Science, Engineering, Business Administration, Business Analytics, Computer Science or related fields, including Supply Chain Engineering.
• Strong programming skills and experience using Python/Pyspark for Data Science.
• Strong analytical techniques, data mining knowledge and proficiency in handling and processing large amounts of data.
• Deep knowledge of statistical and machine learning algorithms.
• Experience in time series forecasting at scale using heuristic-based hierarchical best-fit models, including exponential smoothing, ARIMA, Prophet and custom parameter tuning.
• Experience building scalable machine learning frameworks for demand sensing, including identifying and collecting relevant input data, feature engineering, tuning and testing.
• Experience in price elasticity models, price optimization, market mix modelling and trade promotion optimization.
• Experience applying analytical methods in supply chain and planning, including demand planning, supply planning, market intelligence and optimal assortments, pricing or inventory.
• Strong presentation and communication skills, with the ability to communicate complex analytical or technical concepts to audiences with limited analytical or technical backgrounds.

Nice to have

• Experience with SQL, databases and ETL tools or similar.
• Exposure to distributed data and computing tools including Map/Reduce, Hadoop, Hive, Spark, Gurobi or related Big Data technologies.
• Experience with deep learning frameworks such as Keras, TensorFlow or PyTorch.
• Experience implementing planning applications.
• Understanding of supply chain concepts.
• Experience in time series forecasting.

Details

• Location: Bangalore, Karnataka, India.
• Work from home two days a week.