Data Scientist, Modeler

Teleflora provides innovative marketing, education, and technology to support its member florists. Since 1979, it has grown to the world’s largest flower delivery service with over 10,000 member florists across North America.

We are seeking a Data Scientist to lead forecasting, budgeting, and advanced analytics for our eCommerce business while driving adoption of AI and Large Language Models (LLMs) across analytics and business workflows.

* Local Candidates Only

• Own forecasting models for revenue, orders, conversion rates, 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

• 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
• 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

• Demand forecasting and seasonality
• Customer behavior and conversion drivers
• Leverage GCP/Big Query for large‑scale data analysis
• Identify key drivers of performance across product, pricing, and customer behavior
• 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)

• 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
• 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

• Build models and workflows using:
  • Python (preferred) or R
  • SQL / Big Query (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

• 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 (Big Query 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

• Experience with GCP ecosystem
• Exposure to MLOps or product ionizing models
• Experience in eCommerce or high‑volume consumer environments

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