Data Scientist - OR

Myntra; Bengaluru; On-site; INR 10,00,000 - 15,00,000; Full time

Job summary

A leading e-commerce company in Bengaluru is seeking a Machine Learning Engineer to design and deploy advanced forecasting models. The role requires a strong foundation in data structures and algorithms, proficiency in Python, and experience with ML frameworks like TensorFlow and PyTorch. The ideal candidate will collaborate with cross-functional teams and maintain machine learning pipelines. Exceptional candidates who may not meet every qualification are encouraged to apply.

Qualifications

• 1-3 years of experience with a Master's degree or 2-4 years with a Bachelor's degree.
• Strong foundation in efficient processing of large datasets.
• Knowledge of cloud computing services and distributed systems.

Responsibilities

• Design, develop, and deploy machine learning models for forecasting applications.
• Maintain and optimise machine learning pipelines including data cleaning and model training.
• Implement CI/CD pipelines for automated testing and deployment of ML models.

Skills

Python for data science and machine learning

Optimisation techniques

Data structures and algorithms

Forecasting and time series models

Machine Learning frameworks (TensorFlow, PyTorch)

Communication skills

Education

Master's degree in Statistics, Operations Research, Mathematics, or related

Bachelor's degree in Statistics, Operations Research, Mathematics, or related

Tools

CPLEX

Gurobi

TensorFlow

PyTorch

Scikit-learn

Airflow

Job description

Responsibilities:

• Design, develop, and deploy advanced machine learning models and algorithms for Forecasting, Operations Research, and Time Series applications.
• Build and implement scalable solutions for supply chain optimisation, demand forecasting, pricing, and trend prediction.
• Develop efficient forecasting models leveraging traditional and deep learning-based time series analysis techniques.
• Utilise optimisation techniques for large-scale nonlinear and integer programming problems.
• Hands-on experience with optimisation solvers like CPLEX, Gurobi, COIN-OR, or similar tools.
• Collaborate with Product, Engineering, and Business teams to understand challenges and integrate ML solutions effectively.
• Maintain and optimise machine learning pipelines, including data cleaning, feature extraction, and model training.
• Implement CI/CD pipelines for automated testing, deployment, and integration of machine learning models.
• Work closely with the Data Platforms team to collect, process, and analyse data crucial for model development.
• Stay up to date with the latest advancements in machine learning, forecasting, and optimisation techniques, sharing insights with the team.

Requirements:

• 1-3 years of experience with a Master's degree or 2-4 years of experience with a Bachelor's degree in Statistics, Operations Research, Mathematics, Computer Science, or a related field.
• Strong foundation in data structures, algorithms, and efficient processing of large datasets.
• Proficiency in Python for data science and machine learning applications.
• Experience in developing and deploying forecasting and time series models.
• Knowledge of ML frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Hands-on experience with optimisation solvers and algorithms for supply chain and logistics problems.
• Strong problem-solving skills with a focus on applying OR techniques to real-world business challenges.
• Good to have research publications in Machine Learning, Forecasting, or Operations Research.
• Familiarity with cloud computing services (AWS, Google Cloud) and distributed systems.
• Strong communication skills with the ability to work independently and collaboratively in a team environment.
• Experience with Generative AI and Large Language Models (LLMs).
• Knowledge of ML orchestration tools such as Airflow, Kubeflow, and MLflow.
• Exposure to NLP and Computer Vision applications in an e-commerce setting.
• Understanding of ethical considerations in AI, including bias, fairness, and privacy.
• Exceptional candidates are encouraged to apply, even if they don't meet every listed qualification.