Data Scientist, Modeler

Job Description

• Forecasting & Budgeting (Core Ownership)

• Own forecasting models for:
• Revenue, orders, conversion rates, and AOV
• Marketing performance and demand planning
• Partner with Finance and Leadership on budgeting and planning cycles
• Build scenario models to support strategic decisions
• Continuously improve forecast accuracy using statistical and machine learning techniques

• Customer & LTV Modeling (Core Requirement)

• Design and maintain Customer Lifetime Value (LTV) models
• Perform cohort analysis, retention modeling, and customer segmentation
• Identify key drivers of long-term customer value and profitability
• Partner with Marketing and Product to apply LTV insights to acquisition, retention, and personalization strategies

• AI / LLM Strategy & Implementation

• Lead adoption of AI/LLM capabilities across analytics and business workflows
• Identify and implement use cases such as:
• Automated insight generation and reporting
• Natural language querying (NL → SQL)
• Customer behavior summarization and segmentation
• Build prototypes and scalable solutions using APIs (OpenAI, Claude, Gemini, etc.)
• Critically evaluate AI-generated outputs for accuracy, plausibility, and business relevance

• Advanced Analytics & Modeling

• Develop models for:
• Demand forecasting and seasonality
• Customer behavior and conversion drivers
• Leverage GCP/BigQuery for large-scale data analysis
• Identify key drivers of performance across product, pricing, and customer behavior

• A/B Test Validation & Experimentation Support

• Validate statistical significance and methodology of A/B tests
• Ensure accuracy and consistency of test readouts
• Define guardrails and best practices for experimentation measurement
• Partner with Product and Analytics teams (without owning test execution)

• Communication & Executive Storytelling (Critical)

• Translate complex analyses into clear, actionable insights for non-technical stakeholders
• Develop high-quality presentations and narratives for senior leadership and executives
• Clearly articulate assumptions, risks, and confidence levels in models and forecasts
• Influence decision-making through structured, data-driven storytelling

• Data Strategy & Cross-Functional Collaboration

• Work closely with:
• Data Analytics Manager (India)
• Data Engineering / DW team
• Product, Marketing, and Finance stakeholders
• Help define scalable data models and structures to support analytics and AI use cases

• Tooling & Infrastructure

• Build models and workflows using:
• Python (preferred) or R
• SQL / BigQuery (GCP ecosystem)
• Work with modern AI tooling:
• LLM APIs (OpenAI, Claude, Gemini)
• Help establish scalable pipelines for both traditional ML and LLM-based systems
• Establish best practices for prompt design, validation, and governance

Qualifications

• 5+ years in Data Science or Advanced Analytics (preferably eCommerce or consumer business)
• Experience presenting to senior executives and driving decisions
• Strong experience with:
• Forecasting and time series modeling
• Customer Lifetime Value (LTV) modeling
• Python and SQL (BigQuery preferred)
• Statistical analysis and experimentation
• Proven ability to build executive-level presentations and communicate complex insights clearly
• Hands-on experience with LLMs and AI tools (OpenAI, Claude, Gemini, etc.)
• Experience building or prototyping AI-powered workflows or applications
• Strong ability to evaluate and validate AI-generated outputs for accuracy and plausibility
• Understanding of:
• Prompt engineering
• Model limitations (hallucination, bias, cost tradeoffs)
• Excellent verbal and written communication skills
• Ability to influence stakeholders across Product, Marketing, Finance, and Leadership
• Master's degree (or foreign equivalent) in Data Science or Statistics

Preferred

• Experience with GCP ecosystem
• Exposure to MLOps or productionizing models
• Experience in eCommerce or high-volume consumer environments