Tue, 17 Mar 2026 14:12:16 +0000

Marketing Data Scientist

Department: Marketing

Employment Type: Full Time

Location: Remote

Compensation: $150,000 - $165,000 / year

Description

At Thorne, we work to deliver high-quality, science-backed solutions to empower individuals to take a proactive approach to their well-being. Each day begins with a mission to help others discover and achieve their best health. We count on our team members to challenge and push the boundaries to make that happen. At Thorne, you’ll be joining a team of more than 750 passionate individuals committed to our cause of providing superior health solutions at every age and life stage.

The Marketing Data Scientist will lead modeling and analytics initiatives that improve how we understand, engage, and grow our customer base. This role will focus on building models that uncover insights about customer demographics, behaviors, and preferences to drive more effective marketing strategies.

This role will partner closely with marketing, analytics, and product teams to identify opportunities where modeling can improve targeting, customer engagement, and marketing performance. This role will also own and refine the organization’s Marketing Mix Model while developing new models that enhance customer segmentation, lifecycle marketing, and product insights.

The ideal candidate combines strong statistical and machine learning expertise with the ability to translate analytical findings into clear strategic recommendations for business stakeholders.

RESPONSIBILITIES

Marketing Mix Modeling & Channel Measurement

Own and refine the organization’s Marketing Mix Model (MMM), evaluating current methodology and improving model accuracy and interpretability.

Translate model outputs into actionable insights that inform marketing investment decisions and channel strategy.

Partner with marketing stakeholders to ensure model outputs are effectively incorporated into planning and performance evaluation.

Customer Segmentation & Behavioral Modeling

Develop advanced customer segmentation models that leverage demographic, behavioral, and transactional data to improve targeted marketing strategies.

Build models that identify meaningful customer cohorts, lifecycle stages, and engagement patterns.

Support marketing teams in operationalizing segmentation frameworks that drive personalized marketing and audience targeting.

Marketing Engagement & Journey Modeling

Analyze customer interaction patterns to identify optimal marketing engagement strategies across the customer lifecycle.

Develop models that inform more effective marketing journeys, channel sequencing, and customer touchpoints.

Partner with marketing and data teams to enable activation of model outputs through marketing platforms and customer data infrastructure.

Customer Insights & Sentiment Modeling

Build models that help identify emerging customer needs, sentiment trends, and product opportunities.

Analyze customer feedback, engagement behavior, and other signals to uncover insights that inform marketing strategy and product development.

Provide recommendations on how insights from customer behavior and sentiment can guide new product or feature opportunities.

Model Development & Innovation

Identify new opportunities where statistical or machine learning models can improve marketing effectiveness and customer understanding.

Design and build models using modern data science tools and methodologies.

Continuously evaluate emerging techniques and determine their applicability to marketing and customer analytics.

Stakeholder Partnership

Partner with marketing channel owners and product teams to identify analytical opportunities that support marketing strategy and customer growth.

Present modeling insights and recommendations to marketing leadership and cross-functional stakeholders.

Help build a data-driven culture within marketing by translating complex analyses into actionable business insights.

Vendor & Cross-Functional Collaboration

Collaborate with external partners and vendors that support modeling, machine learning engineering, or advanced analytics initiatives.

Partner with internal analytics, engineering, and data platform teams to ensure models can be integrated into data infrastructure and marketing activation workflows.

WHAT YOU NEED

Required Competencies:

Bachelor’s degree in a quantitative field such as Statistics, Data Science, Mathematics, Economics, Computer Science, Engineering, or a related discipline.

4+ years of experience in data science, marketing science, econometrics, or a related quantitative field.

Strong experience building statistical or machine learning models using Python or R.

Experience developing customer segmentation, clustering, or behavioral models.

Strong foundation in statistical techniques such as regression, clustering, classification, and causal analysis.

Strong SQL skills and experience working with large datasets in cloud data environments.

Ability to communicate complex analytical findings clearly to non-technical stakeholders.

Preferred Competencies/Experience:

Master’s or PhD in Statistics, Data Science, Economics, Applied Mathematics, Computer Science, or a related quantitative field.

Experience working with marketing or customer analytics data.

Experience building models that support audience targeting, lifecycle marketing, or personalization.

Familiarity with marketing technology platforms, customer data platforms (CDPs), or marketing activation tools.

Experience collaborating with external modeling or data science vendors.

Experience operationalizing models in production or working alongside ML engineering teams.

WHAT WE OFFER

Competitive compensation

100% company-paid medical, dental, and vision insurance coverage for employees

Company-paid short- and long-term disability insurance

Company- paid life insurance

401k plan with employer matching contributions up to 4%

Gym membership reimbursement

Monthly allowance of Thorne supplements

Paid time off, volunteer time off and holiday leave

Training, professional development, and career growth opportunities

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