Sr. Manager of Analytics and Data Science
Indexed description
- 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
- 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
- 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
- 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
- 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
- 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
- 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 consumer/operations experience preferred
- Deep proficiency in machine learning, statistical modeling, experimentation/A/B testing, forecasting, and optimization techniques
- Strong programming and data fluency with Python and/or R, advanced SQL, and modern data platforms (e.g., Snowflake, Databricks, or comparable cloud data warehouses)
- Working knowledge of cloud environments (AWS, Azure, or GCP) and MLOps practices for deploying, monitoring, and maintaining models at scale
- Proficiency with BI and visualization tools (e.g., Tableau, Power BI, Sigma) to communicate insight clearly to business audiences
- Familiarity with generative AI and large language model applications and their responsible, value-driven use in the enterprise
- Proven ability to build, scale, mentor, and retain high-performing technical teams
- Strong business acumen with the ability to connect analytical work to financial and operational outcomes
- Excellent written and verbal communication skills, including the ability to make complex concepts clear and compelling to senior, non-technical leadership.
- Skilled at prioritization, roadmap planning, and resource management across competing demands
- Self-directed leader who thrives in a fast-moving, collaborative, and evolving environment
Love's is an Equal Opportunity Employer. Veterans encouraged to apply.
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