Lead Data Scientist – Merchandising & Pricing

Role Overview

• Lead design and implementation of advanced data science algorithms that improve merchandising and pricing business decisions, including building models for Demand forecasting, Assortment optimization, Price elasticity, and Inventory allocation and replenishment.
• Designing and deploying demand forecasting algorithms that go beyond univariate time series to multivariate and hierarchical forecasts for predicting long range, multi-echelon sales forecasting.
• Develop & Implement AI/ML driven assortment selection algorithms that learn from user behavior & preferences.
• Collaborate with product & data engineers to identify data for modeling, and transform datasets as required for effective modeling.
• Build, scale and deploy robust Machine Learning models leveraging Classification, Regression, and Clustering.
• Develop models to process historical and large datasets to understand model Price elastic demand for products, categories, channels and customer segments using predictive and causal modeling techniques.
• Collaborate with analytics, product and business teams to champion a test-and-learn approach.

Requirements

• Master's Degree or Equivalent Level in quantitative fields like computer science, engineering, physics, mathematics, etc.
• 6+ years of experience in the field with at least 2-3 years of being the main technical lead in related projects
• Experience working with SOTA machine learning, deep learning (LSTM, Transformers), Optimization models for retail and ecommerce use cases driving efficiency in operations and customer value.
• Experience with Large Language models and Generative AI and Agents.
• Bonus if specific experience in operations research.
• Experience in ML Ops model monitoring, retraining, CI/CD, and experiment tracking
• Extensive experience using common machine learning and deep learning frameworks such as TensorFlow, PyTorch, OpenAI, and LangChain
• Expert understanding of Python and other common languages.
• Expert level experience in cloud platforms like Databricks, GCP, and offers like Azure ML, Vertex AI.
• Experience being the technical lead of multiple projects at the same time, responsible for delivery and business metrics
• Experience in an Agile working environment and at least one related project management tool (Azure, DevOps, Jira, etc.)
• Previous experience mentoring, training, and developing junior members of the team through technical influence.
• Experience with software engineering principles as it relates to Machine Learning systems.
• Comfortable presenting results to and influencing senior and executive leadership on strategic technical decisions, from the lens of science.
• Brings a collaborative, problem solving and growth mindset to all interactions with a strong focus on delivery.

Tech Stack

• Azure
• Cloud
• Google Cloud Platform
• Python
• PyTorch
• Tensorflow

Benefits

• health insurance
• retirement plans
• paid time off
• flexible work arrangements
• professional development
• bonuses
• generous suite of benefits