Weekend Data Science Jobs in Novi, MI (NOW HIRING)

Domino’s is a purpose-inspired, performance-driven company powered by exceptional people who are committed to feeding the power of possible—one pizza at a time. Founded in 1960 as a single store in Ypsilanti, Michigan, Domino’s has grown into the largest pizza company in the world, with more than 22,300 stores across 90+ markets. Our success is built on the strength of our people, technology, and franchise system. As a leader in innovation, we continue to transform the pizza and QSR industry while creating opportunities for team members to learn, grow and thrive. If you're ready to make an impact, build a meaningful career and help shape what's next, there's a place for you at Domino's.

The Decision Science team drives Domino’s industry-leading growth by pairing strong business thinking with advanced analytics across data science, experimentation, and applied measurement. The team partners closely with Marketing, Loyalty, Product, and Technology to turn data into clear direction that improves customer engagement, loyalty health, and long-term retention.

The Senior Data Scientist – Loyalty & Ecommerce Analytics plays a critical role in shaping how Domino’s evaluates and evolves its loyalty and digital experience strategy. This role operates at the intersection of loyalty mechanics, promotions, and ecommerce behavior, delivering insights that inform campaign design, product decisions, and long-term customer value. This role works independently on complex, cross-functional problems, applying deep analytical judgment to ambiguous questions and imperfect data. Success in this role requires strong technical depth, business fluency across loyalty and ecommerce, and the ability to translate analysis into clear, credible narratives that influence decision making and build alignment across teams.

• Own and set direction for complex analyses spanning loyalty performance, perks, lifecycle behavior, eComm AB tests, and ecommerce funnels
• Develop and interpret perk projections, Active Member reporting, and post‑campaign analyses to inform campaign selection and prioritization
• Apply advanced analytical techniques and sound judgment when clean experimental controls are not available

• Frame ambiguous business questions into structured analytical approaches that span loyalty and ecommerce considerations
• Connect results to business context, clearly articulating assumptions, tradeoffs, and implications for decision‑making
• Deliver clear memos and presentations that synthesize insights for Marketing, Loyalty, Product, and Technology partners

• Act as a resource and thought partner to peers and stakeholders across Loyalty, Digital Experience, and Product teams
• Explain complex or sensitive findings and work to build alignment and consensus across teams
• Establish strong working relationships with subject matter experts across functions to drive shared outcomes

• Help advance the team’s analytics practice by adopting AI-enabled tools, automation, and modern workflows where they meaningfully improve insight generation and scale
• Contribute reusable frameworks, templates, and analytical patterns that raise team standards and efficiency

• Owns and sets direction for complex analytical problems end to end, independently defining approach, success criteria, and decision framing while proactively engaging peers and leadership as needed
• Exercises seasoned judgment across multiple sources of information, deliberately selecting methods, tradeoffs, and level of rigor based on business risk, scale, and downstream implications
• Raises the bar across the team by modeling strong analytical thinking, elevating storytelling standards, and coaching others to challenge assumptions and strengthen conclusions
• Extends impact beyond individual work by establishing reusable frameworks, shared context, and analytical patterns that improve consistency, efficiency, and quality across the team
• Builds deep trust with partners by delivering insights that are reliable, well‑reasoned, and clearly connected to business realities, tradeoffs, and decision paths

• Bachelor’s Degree in Data Science, Statistics, Mathematics, Marketing Science, or related field
• 3+ years of professional related data science experience
• Advanced knowledge of a web‑analytics tools like Adobe Analytics or similar products
• Proficient in SQL querying, with ability to clean, transform, and process data
• Proficient in R or Python, with emphasis on statistical analysis.
• Applied experience with statistical testing, with firm understanding of test design
• Proficient in Microsoft Office – Fluent in Power Point, Excel, and PowerBI or similar products
• Excellent project management and collaboration skills

Benefits:

• Paid Holidays and Vacation
• Medical, Dental & Vision benefits that start on the first day of employment
• No-cost mental health support for employee and dependents
• Childcare tuition discounts
• No-cost fitness, nutrition, and wellness programs
• Fertility benefits
• Adoption assistance
• 401k matching contributions
• 15% off the purchase price of stock
• Company bonus