Job Description :

What you'll do :

- Design, build, deploy and refine large-scale machine learning models and algorithmic decision-making systems that solve real-world problems for customers.

- Work cross-functionally with commercial stakeholders to understand business problems or opportunities and develop appropriately scoped analytical solutions.

- Collaborate closely with various engineering, infrastructure, and ML platform teams to ensure adoption of best-practices in how we build and deploy scalable ML services.

- Identify new opportunities and insights from the data (where can the models be improved, what is the projected ROI of a proposed modification).

- Be obsessed with the customer and maintain a customer-centric lens in how we frame, approach, and ultimately solve every problem we work on.

We Are a Match Because You Have :

- 3+ years of industry experience with a Bachelor/ Master s degree or minimum of 1-2 years of industry experience with PhD in Computer Science, Mathematics, Statistics, or related field.

- Strong theoretical understanding of statistical models such as regression, clustering and ML algorithms such as decision trees, neural networks, etc.

- Solid understanding of algorithms for search retrieval, ranking, relevance, query understanding, NLP, or recommender systems.

- Good proficiency in the Python ML ecosystem (pandas, NumPy, scikit-learn, XGBoost, etc.).

- Solid hands-on expertise deploying machine learning solutions into production.

- Strong written and verbal communication skills.

- Intellectual curiosity and enthusiasm about continuous learning.

Nice to have :

- Experience in e-commerce, or online search systems.

- Knowledge of modern NLP techniques (transformers, embeddings, semantic search).

- Experience applying Generative AI / LLMs (e.g., GPT, LLaMA) to real-world problems such as search, personalization, or content generation.

- Experience with deep learning frameworks like PyTorch.

- Familiarity with vector databases, information retrieval frameworks (e.g., Elasticsearch, Vespa).

- Familiarity with GCP (or AWS, Azure), ML model development frameworks, ML orchestration tools (Airflow, Kubeflow or MLFlow).

- Experience with Apache Spark Ecosystem (Spark SQL, MLlib/Spark ML).

Role Details :

- Role : Data Science & Machine Learning - Other

- Industry Type : Retail

- Department : Data Science & Analytics

- Employment Type : Full Time, Permanent

- Role Category : Data Science & Machine Learning