Data Scientist, Modeler at Teleflora — NeverHard

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