Senior Data Scientist

We are seeking a Senior Data Scientist to join our Digital Analytics team within the E-commerce division. Our team facilitates data-driven decision-making across our digital platforms, accelerating strategic outcomes through advanced analytics. We move beyond descriptive metrics by integrating data science and experimentation to deeply understand and influence user behavior.

By embedding these capabilities into our digital ecosystem, we drive personalization, intelligent features, and large-scale optimization. We integrate data throughout the entire product lifecycle to ensure every update provides significant value to both users and the organization.

As a Senior Data Scientist, you will be instrumental in exploring datasets, generating actionable insights, and developing data-driven product experiences. You will collaborate closely with product managers, engineers, and analysts to deploy predictive and prescriptive models that directly enhance customer experience and business results.

This is a product-centric role: we are looking for a professional who balances rigorous analytical thinking with applied data science. You should be adept at navigating the full process—from initial hypothesis generation and exploration to modeling and impact measurement—with a constant focus on delivering concrete results in a production environment.

Key Responsibilities

• Develop Advanced Analytics Solutions: Design and deploy machine learning models using predictive and prescriptive analytics to resolve complex digital commerce and user experience challenges.

• End-to-End Use Case Management: Convert business requirements into technical data science strategies. Lead the entire lifecycle from initial discovery and modeling to production deployment and iterative refinement. Ensure continuous monitoring to maintain model accuracy and business relevance.

• Strategic Data Exploration: Proactively investigate large datasets to identify emerging user trends, behavioral patterns, and high-growth opportunities.

• Production-Ready Collaboration: Work in synergy with product and engineering departments to launch scalable, reliable solutions that drive measurable organizational impact.

Technical Stack

• Data Processing & Modeling: Databricks, Spark / PySpark, SQL, Python

• Frameworks & Tools: TensorFlow / PyTorch, MLflow, Jupyter Notebooks, Git

• Analytics & Visualization: Product analytics tools (Amplitude style), Experimentation platforms (Statsig style), Tableau

What You Will Bring

• Full-Lifecycle Ownership: Proven ability to manage data science projects from hypothesis generation and feature engineering to experimentation, deployment, and long-term optimization. You can translate complex data findings into actionable insights that guide product roadmaps.

• Applied Data Science Expertise: Hands-on experience in designing and interpreting A/B tests and multivariate experiments. You excel at applying statistical modeling to real-world scenarios such as personalization, conversion optimization, and user engagement.

• Product-Driven Mindset: Experience in high-growth digital environments with a focus on optimizing user journeys and tracking impact against core business KPIs.

• Technical Proficiency:

  • Advanced programming in Python (Pandas, NumPy, Scikit-learn).

  • Strong capability in handling large-scale data via SQL and Spark.

  • Familiarity with deep learning frameworks is a significant advantage.

• Collaboration & Communication: Ability to bridge the gap between technical and non-technical stakeholders (Product Managers, Engineers, Designers) to drive informed decision-making.