Data Scientist, Marketing & eCommerce — United States

This is a Fully Remote Job

About Our Client:

The organization operates within the floral delivery industry, addressing the challenge of connecting consumers with local florists through innovative marketing, education, and technology. It supports a nationwide network of more than 10,000 member florists across North America, facilitating hand-arranged and hand-delivered bouquets. As the largest flower delivery service globally, the program focuses on providing florists with resources to thrive while ensuring customers receive quality floral products.

About the Opportunity:

The DATA SCIENTIST, MARKETING & ECOMMERCE role is focused on building and maintaining predictive Customer Lifetime Value (LTV) models and developing statistical and machine learning models to forecast eCommerce performance. This position plays a critical role in forecasting revenue, analyzing customer behavior, and identifying opportunities to improve customer acquisition, retention, and profitability. The role involves collaboration with Marketing, Finance, Product, and Data Engineering teams to support data-driven business decisions and explore emerging AI technologies to enhance analytics and workflows.

Responsibilities:

• Design, build, validate, and maintain predictive Customer Lifetime Value models using customer transaction and behavioral data.

• Develop statistical and machine learning models to predict customer value, purchasing frequency, repeat purchases, and retention.

• Perform cohort analysis and customer segmentation to identify purchasing trends and customer value.

• Continuously improve model accuracy and predictive performance.

• Collaborate with marketing and product teams to apply LTV predictions to acquisition and retention strategies.

• Develop and maintain models to forecast eCommerce metrics including revenue, orders, conversion rates, and average order value.

• Analyze trends, seasonality, marketing performance, and customer behavior to identify key business drivers.

• Build scenario models to evaluate growth opportunities and risks.

• Support budgeting, forecasting, and strategic planning with finance and marketing teams.

• Analyze large datasets to identify trends and opportunities across eCommerce operations.

• Use Python, SQL, and cloud platforms to build and optimize predictive models.

• Collaborate with data engineering teams to ensure data quality and accessibility.

• Explore and test AI and Large Language Model technologies to improve analytics and business workflows.

• Communicate findings and recommendations to business stakeholders.

Requirements:

• Minimum 3 years of experience in data science and predictive modeling within eCommerce, direct-to-consumer, subscription, or digital consumer businesses.

• Proven ability to independently design, build, and validate Customer Lifetime Value models using transaction and behavioral data.

• Strong skills in developing statistical and machine learning models for revenue forecasting, purchasing behavior, and retention.

• Advanced proficiency in Python and SQL.

• Experience with cohort analysis and customer segmentation.

• Ability to translate modeling results into actionable business insights.

• Master’s degree in Data Science, Statistics, or a related quantitative field, or equivalent practical experience.

Preferred Qualifications:

• Experience with Google Cloud Platform and BigQuery.

• Familiarity with AI, Large Language Models, or generative AI applications.

Pay Range and Compensation Package:

• The pay range and compensation package for this role will be determined based on the candidate's experience, skills, and other relevant factors.

Equal Opportunity Statement: Our client is an equal opportunity employer. They celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, or national origin.

Note:

ypMW875Td is a recruitment partner of this role. Please note that all employment decisions, including candidate assessment, interviews, hiring, compensation, and employment terms, are made exclusively by the hiring employer.