Personalization Data Science Senior Manager

3 weeks ago

Ann Arbor Michigan, United States Domino's Corporate Full time
Job Description

The Digital Data Science team at Domino’s is looking for a proven Data Science Senior Manager, who will come in as a proven and experienced technical expert in the field of Marketing and Customer Data Science to lead ML initiatives to drive meaningful business results via Personalization. Leveraging data and modeling to improve each customer’s experiences across the entire digital space is a key focus area for the company, and the team is excited about the endless possibilities to tackle. The candidate we seek is somebody who thrives in navigating through ambiguity, passionate and driven about the Personalization space, possessing a strong action-bias and can-do attitude, and a culture leader who will elevate and energize the whole team along the journey. Strong executive presence and ability to articulate complex ideas in easily understandable terms to diverse and executive audiences will also be key. The ability to not only build top-of-the-line models (LTV, Churn, Promo recommendation), but also successfully collaborate with technical data teams, as well as Marketing and Business teams and leadership will be critical.   

Main responsibilities

 

Technical Leadership and Guidance 

 

Thought leader – The team will rely on your expertise as a technical authority in the realm of Personalization Data Science. Your role will include consistently presenting innovative ideas of high quality and quantity to inspire and generate solutions. Inspire team members to build a culture that will help enable Domino’s A&I team to be the most admired DS team in the QSR industry (socializing work, writing blog posts, recruiting talent, etc).

Lead from the front – Proactively scope out solutions and approaches, with a can-do energy and passion that will be infectious to your team. Supply the resources and expertise necessary to bring along team members and more. 

Be hungry – Stay informed about industry trends and advancements in marketing personalization, digital innovation, and machine learning to guide internal strategies. Cultivate a culture that embraces technological advancement and risk-taking and pave the way for pioneering ML/AI breakthroughs at Domino’s.  

 

 

Modeling 

 

Ability to quickly navigate through, understand, and work with data in all shapes and forms to chart the course on how to ship ML models end-to-end.  

Developing and shipping LTV, Churn Prediction, and Promo Recommendation Engine models and systems.

Knowledge of deep technical insights aiding in the appropriate selection of and use of machine learning algorithms. 

Open-minded and flexible, knowing how to build both ML models of incredible complexity and accuracy, but also ‘scrappy and quick’ ML models (80/20 principle), depending on the business need.  

Project management and leadership ability in modeling: the ability to collaborate, delegate, and break big modeling projects down into smaller deliverable increments and iterations.  

 

 

Strategic Planning, Collaboration, and Alignment 

 

Bridge business strategy with technical execution, aligning ML initiatives with Personalization, Digital Innovation, and broader business goals. 

Collaborate at all levels from IT to Finance to Innovation to Marketing. We are team players and win together at Domino’s.  

Lead strategic planning across ML initiatives, ensuring alignment with Domino's overarching strategic objectives and long-term vision. 

Manage multiple technical projects simultaneously and ensure seeing plans successfully through to completion and impact.

Leverage past experiences deploying ML models into production environments, seamlessly collaborating with ML Ops and Engineer teams to ensure our models can scale.

Communicate with and present to SVP+ and C-suite members, articulating complex ideas in an easily understandable and digestible manner.

 

Managerial Duties 

 

Take ownership of and demonstrate genuine commitment to fostering the professional growth and development of two individual contributor Data Scientist reports.  

Provide regular 1-1s and coaching sessions to foster professional growth and address areas of improvement. 

Oversee performance appraisal process for direct reports, ensuring fair and constructive feedback. 

Maintain a commitment to ongoing self-improvement in leadership and managerial skills, in a manner similar to staying abreast of emerging technologies.  

Continue to prioritize and address any team-related concerns and foster a positive, collaborative, and innovative work environment. 

Be capable of managing smaller teams as well as larger teams (6+); leverage past experience leading teams of diverse talent and skillsets (analysts, data scientists, engineers, machine learning specialists)

 

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