Key Responsibilities:

• Research, prototype, and develop algorithms and solutions to solve problems across retail.
• Work with tabular customer and transaction data to produce insights and analysis.
• Stay up to date with emerging technologies and learn new techniques/libraries/frameworks.
• Build and deploy algorithms and statistical solutions into production ready systems.
• Deliver on time with a high bar on quality of research, innovation, and engineering.

Basic Qualifications:

• Strong knowledge of the fundamentals of statistics and machine learning theories.
• 2 years of experience developing ML systems in cloud environments (AWS/Azure), preferably Databricks.

• 2 years of hands-on experience with machine learning tools and libraries (scikit-learn, TensorFlow/Keras, PyTorch, Huggingface, AWS Sagemaker and/or Databricks etc.)

• 2 years of experience building data engineering pipelines and performing exploratory data analysis on large datasets.
• 1 years of experience building and deploying software/models to production.
• Bachelor s Degree or higher in Computer Science/Engineering/Math, or relevant experience.

Preferred Qualifications:

• PhD in Statistics, AI, or Machine Learning (or) MS in Statistics, AI, or Machine Learning with 2 years or more of industry experience.
• Experience working on Databricks platform for ML solutioning, deployments and data engineering is a plus.
• Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance.
• Published research or Patents in machine learning, system design or data engineering.
• Impact on the AI community through conference presentations, blog posts or open-source contributions.