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The Wonderful Company

Markets consumer foods, beverages, and florals

Data Scientist - Marketing & Ecommerce

Data SciencePosted on Nov 6
Full-timeHouston, TX, USA$100k - $135kIn-person

About the Job

Requirements

  • At least 3 years of hands-on experience in data science and predictive modeling, including experience supporting an eCommerce, direct-to-consumer, subscription, or digital consumer business.
  • Experience independently designing, building, and validating predictive Customer Lifetime Value (LTV/CLV) models that estimate future customer value using transaction and behavioral data.
  • Experience developing statistical and machine learning models for eCommerce revenue forecasting, customer purchasing behavior, and retention.
  • Advanced proficiency in Python and SQL, with demonstrated experience developing predictive models using customer-level datasets.
  • Experience applying statistical modeling and machine learning techniques to customer behavior, purchase frequency, and retention prediction.
  • Understanding of model development, validation, performance evaluation, and continuous improvement.
  • Experience conducting cohort analysis and customer segmentation to support customer analytics.
  • Ability to translate predictive modeling results into actionable recommendations for Marketing, Finance, and Product teams.
  • A master's degree in Data Science, Statistics, or a related quantitative field, or equivalent practical experience.

Responsibilities

  • Independently design, build, validate, and maintain predictive Customer Lifetime Value (LTV/CLV) models using customer transaction and behavioral data.
  • Develop statistical and machine learning models to predict future customer value, purchasing frequency, repeat purchases, and retention.
  • Apply predictive modeling techniques to estimate customer value over time and identify factors influencing long-term profitability.
  • Perform cohort analysis and customer segmentation to identify trends in purchasing behavior and customer value.
  • Evaluate and continuously improve model accuracy, reliability, and predictive performance.
  • Partner with Marketing and Product teams to apply LTV predictions to customer acquisition, retention, and marketing investment decisions.
  • Develop and maintain statistical and machine learning models to forecast eCommerce revenue, orders, conversion rates, average order value (AOV), and customer demand.
  • Analyze historical trends, seasonality, marketing performance, and customer behavior to identify key drivers of business performance.
  • Build scenario models to evaluate growth opportunities, business risks, and potential outcomes.
  • Partner with Finance and Marketing to support budgeting, forecasting, and strategic planning.
  • Continuously evaluate and improve forecast accuracy and model performance.
  • Analyze large datasets to identify trends, patterns, and opportunities across eCommerce operations.
  • Apply statistical analysis and machine learning techniques to understand customer behavior, purchasing patterns, conversion drivers, and marketing effectiveness.
  • Leverage Python, SQL, and cloud-based data platforms to build, test, and optimize predictive models.
  • Collaborate with Data Engineering and Analytics teams to ensure data quality, consistency, and accessibility.
  • Support the development of scalable data models and analytical workflows.
  • Explore opportunities to apply AI and Large Language Model (LLM) technologies to improve analytics, reporting, and business workflows.
  • Collaborate with internal teams to identify potential AI use cases and evaluate their business value.
  • Develop familiarity with emerging AI tools, technologies, and applications.
  • Participate in the development and testing of AI-powered analytics solutions as these capabilities evolve.
  • Partner with Marketing, Finance, Product, and Analytics teams to understand business challenges and develop data-driven solutions.
  • Work closely with Data Engineering and Data Warehouse teams to support analytical initiatives.
  • Communicate model findings, assumptions, and recommendations to business stakeholders.
  • Contribute to analytical best practices and continuous improvement initiatives.

Desired Qualifications

  • Experience with Google Cloud Platform (GCP) and BigQuery.
  • Familiarity with AI, Large Language Models (LLMs), or generative AI applications, with an interest in developing AI-powered analytics solutions.
  • Experience deploying predictive models into production environments.

About the Company

The Wonderful Company

Markets consumer foods, beverages, and florals

The Wonderful Company is a privately held, diversified consumer goods group based in Los Angeles. It grows, processes, bottles, and distributes a wide range of food and beverage products and services, including Wonderful Pistachios, Wonderful Halos mandarins, POM Wonderful pomegranate products, FIJI Water, JUSTIN wines, and Teleflora floral deliveries. Its products are produced through farming, processing, bottling, and distribution that bring goods from orchards, vineyards, and water sources to consumers around the world. The company differentiates itself through large market leadership across multiple categories, a vertically integrated supply chain, and a strong emphasis on health and sustainability, backed by substantial charitable giving and CSR. Its goal is to improve people’s health and well-being by offering wholesome foods and beverages at scale while investing in environmental stewardship and community programs.

Company size
1,001-5,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Los Angeles, CA
Founded
1979

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