Sr. Manager of Analytics and Data Science

Sr. Manager of Analytics and Data Science

Location:

Oklahoma City, OK, US, 73120

Welcome to Love's:
The Senior Manager of Analytics & Data Science leads teams of analytics and data science professionals responsible for delivering enterprise-wide insights, advanced analytics, and scalable solutions that drive strategic decision-making across the organization. This leader partners closely with business and technology stakeholders to identify opportunities, solve complex business challenges, and deliver measurable business impact through data.

• Drive Strategic Decision-Making Through Analytics
• Partner with leaders across the organization to identify opportunities where analytics can improve business performance and support strategic objectives
• Translate complex business questions into actionable analytical approaches and measurable outcomes
• Deliver insights and recommendations that influence decision-making at all levels of the organization
• Promote the use of data and analytics as strategic assets across the enterprise
• Advanced Analytics & Solution Delivery
• Oversees the entire lifecycle of analytics projects, including requirement gathering, development, validation, deployment, and monitoring of advanced analytics, machine learning, and AI-enabled solutions
• Ensures analytical solutions are scalable, actionable, and aligned to business objectives while delivering measurable business value
• Establishes best practices that drive consistency, quality, and adoption across analytics initiatives
• Guides teams in balancing technical rigor with practical business application to maximize organizational impact
• Team Leadership & Development
• Build and scale a high-performing data science & analytics organization, defining roles, career paths, and operating norms that attract and retain top analytical talent
• Lead a team of data scientists, seen as trusted advisors, known for proactive insights and creating thought leadership
• Foster a culture of curiosity, accountability, analytical rigor, experimentation, and continuous improvement
• Collaborate cross-functionally with Customer Experience, FP&A, and Data Engineering to deliver comprehensive solutions
• Provide coaching, performance management, and career development opportunities that support employee growth and engagement
• Establish clear priorities and create an environment that enables teams to perform at their highest level
• Strategic Analytics Roadmap
• Define and evolve the enterprise analytics roadmap in alignment with organizational priorities
• Evaluate and prioritize initiatives to maximize business impact and resource effectiveness
• Balance short-term business needs with long-term capability development
• Identify opportunities to expand analytics capabilities and increase organizational value
• Strengthen Enterprise Partnerships
• Develop trusted relationships with stakeholders across operations, finance, marketing, merchandising, customer experience, technology, and other business functions
• Align analytics investments with enterprise priorities and strategic goals
• Facilitate collaboration between analytics, technology, and business teams to maximize impact
• Effectively communicate complex analytical concepts to technical and non-technical audiences, including senior leadership
• Data Governance & Quality
• Partner with technology and data teams to improve data quality, governance, accessibility, and trustworthiness
• Advocate for data standards and best practices that support enterprise analytics
• Ensure analytical solutions are built on reliable, well-governed data foundations
• Promote confidence and trust in analytical outputs across the organization
• Innovation & Continuous Improvement
• Champion the adoption of emerging analytics, automation, and AI-enabled capabilities that improve business outcomes, accelerate insight generation, and enhance team effectiveness
• Encourage experimentation and continuous improvement in analytical approaches and methodologies
• Partner with technology teams to evaluate and apply emerging capabilities that enhance analytics effectiveness
• Maintain awareness of industry trends and identify opportunities to create value through innovation

Bachelor's degree required in a quantitative or technical field (e.g., data science, statistics, mathematics, computer science, economics, engineering, or operations research);
Master's or PhD strongly preferred

8+ years of progressive experience in data science, advanced analytics, or quantitative modeling, including hands-on delivery of machine learning and statistical models in a production environment

3+ years of direct people-leadership experience managing and developing teams of data scientists and analysts

Demonstrated track record of translating ambiguous business problems into analytical solutions that drive measurable, enterprise-level impact

Experience partnering with executive and cross-functional stakeholders to set strategy and influence decisions without direct authority

Retail, fuel, hospitality, or large-scale…