Data Scientist, Modeler 27

The Wonderful Company is hiring a Data Scientist in Montana to lead forecasting, budgeting, and analytics for their eCommerce business, focusing on AI adoption. Responsibilities include developing forecasting models, customer LTV modeling, and supporting A/B testing. The role requires translating complex analyses for non-technical stakeholders. This position is hybrid, requiring in-office work Monday to Wednesday, with remote work options on Thursday and Friday.
Teleflora provides innovative marketing, education, and technology to make sure our member florists get the resources they need to thrive, creating beautiful bouquets with keepsake vases delivered to your door. We've been a part of The Wonderful Company family since 1979, and with a nationwidenetwork of florists, we've become the world's largest flower delivery service. With more than 10,000 member florists in North America, we lead the industry by working directly with our florists to hand-arrange and hand deliver every bouquet!

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

This role combines traditional data science (forecasting, LTV modeling, experimentation validation) with emerging AIcapabilities to unlock new efficiencies and insights. A key aspect of this role is the ability to translate complex analyses into clear, compelling narratives for non-technical stakeholders, including senior leadership. The Data Scientist will also support A/B testing by validating results, while not owning test execution.

This position will be based at our West Los Angeles, CA office. We work a hybrid schedule with an in-office requirement Monday-Wednesday and the option to work remotely on Thursday and Friday.

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) modelsPerform 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 relevanceAdvanced 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 stakeholdersDevelop 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 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) modelingPython and SQL (BigQuery preferred) Statistical analysis and experimentation Proven ability to build executive-level presentations and communicate complex insights clearlyHands-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 plausibilityUnderstanding of: Prompt engineering Model limitations (hallucination, bias, cost tradeoffs) Excellent verbal and written communication skills Ability to influence stakeholders across Product, Marketing, Finance.