Data Scientist, Modeler

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