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Senior Manager Data Analytics Jobs in Springfield, MO

Mid - Senior Level This is what you will do.. You will be using quantitative methods to assess the ... Who has nearly 5+ years of experience in the analysis of Marketing data using SAS and other ...

Senior Data Engineer I

Springfield, MO · On-site

$96K - $131K/yr

The Senior Data Engineer transforms data into a useful format for analysis and is focused on the ... The Senior Data Engineer will design, build, integrate data from various resources and manage big ...

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Senior Manager Data Analytics information

See Springfield, MO salary details

$40.9K

$104.1K

$153.3K

How much do senior manager data analytics jobs pay per year?

As of Sep 14, 2026, the average yearly pay for senior manager data analytics in Springfield, MO is $104,127.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,000.00 and $122,800.00 per year, depending on experience, location, and employer.

What does a senior manager data analytics do?

A Senior Manager Data Analytics leads teams that analyze large sets of data to help organizations make informed business decisions. They develop analytics strategies, oversee data projects, and ensure the quality and integrity of data-driven insights. This role often involves collaborating with other departments, mentoring analysts, and presenting key findings to senior leadership. Senior Managers in this field need strong technical skills, leadership abilities, and business acumen to drive impactful results.

What are the key skills and qualifications needed to thrive as a senior manager data analytics?

To thrive as a Senior Manager Data Analytics, you need advanced expertise in data analysis, statistical modeling, and business intelligence, typically supported by a degree in a quantitative field and several years of analytics experience. Proficiency with analytics tools such as SQL, Python, R, and platforms like Tableau or Power BI, as well as experience with data warehousing systems, is essential. Strong leadership, strategic thinking, and communication skills enable you to guide teams and translate complex findings into actionable business insights. These competencies are crucial for driving data-informed decision-making and maximizing organizational value from analytics initiatives.

How does a senior manager data analytics typically collaborate with cross-functional teams within an organization?

Senior Managers of Data Analytics frequently work alongside cross-functional teams such as IT, product development, marketing, and finance to ensure that data-driven insights align with business objectives. They are responsible for translating complex analytical findings into actionable recommendations and communicating these insights clearly to both technical and non-technical stakeholders. Regular collaboration often involves leading meetings, setting project priorities, and ensuring data initiatives are integrated smoothly with ongoing business strategies. This collaborative environment fosters innovation and helps drive organizational growth.

What is the difference between Senior Manager Data Analytics vs Data Analyst?

AspectSenior Manager Data AnalyticsData Analyst
Required CredentialsBachelor's/Master's in Data Science, Analytics, or related field; extensive experienceBachelor's degree in related field; entry to mid-level experience
Work EnvironmentLeadership roles, strategic planning, team managementData collection, analysis, reporting
Employer & Industry UsageCorporate, finance, healthcare, tech companiesVarious industries, including marketing, finance, tech
Common Search & ComparisonOften compared for leadership and strategic rolesCompared for technical and analytical skills

The main difference between Senior Manager Data Analytics and Data Analyst lies in their responsibilities and experience level. Senior Managers focus on strategic oversight, team leadership, and decision-making, while Data Analysts handle data collection, analysis, and reporting at a more technical level. Senior Managers typically have more experience and credentials, working in leadership roles within organizations across various industries.

What are popular job titles related to Senior Manager Data Analytics jobs in Springfield, MO?

For Senior Manager Data Analytics jobs in Springfield, MO, the most frequently searched job titles are:

What job categories do people searching Senior Manager Data Analytics jobs in Springfield, MO look for?

The top searched job categories for Senior Manager Data Analytics jobs in Springfield, MO are:

What cities near Springfield, MO are hiring for Senior Manager Data Analytics jobs?

Cities near Springfield, MO with the most Senior Manager Data Analytics job openings:

Sr. Manager, Data Science & Applied AI

Springfield, MO • On-site

O'Reilly Auto Parts
Individual, Family and Community Social Assistance • 10K+ employees

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 15 days ago


O'Reilly Auto Parts rating

5.2

Company rating: 5.2 out of 10

Based on 1,921 frontline employees who took The Breakroom Quiz


Job description

The Sr. Manager, Data Science & Applied AI is a strategic and technical leader responsible for leading Data Science and Applied AI capabilities across multiple business domains, including People Analytics, Inventory Optimization, Supply Chain, Operations, and Generative AI.
This leader will manage and develop high-performing Data Science teams while establishing the strategy and technical direction for Machine Learning, Applied AI, Generative AI, and advanced analytics solutions. The role partners closely with business, product, data engineering, architecture, and technology leaders to translate complex business opportunities into scalable AI-driven solutions with measurable business outcomes.
The ideal candidate combines strong AI/ML and GenAI technical depth with retail business acumen, particularly across Inventory, Supply Chain, Store Operations, Merchandising, Workforce/People Analytics, and other operational functions.
This is an on-site position located in Springfield, MO. Remote work is not an option for this role.
Key Responsibilities
  • Lead multiple Data Science and Applied AI teams supporting business domains such as People Analytics, Inventory Optimization, Supply Chain, Operations, and Generative AI.
  • Define and execute the enterprise strategy for Applied AI, Machine Learning, Generative AI, predictive analytics, and optimization across supported business domains.
  • Identify high-value business opportunities where AI can improve inventory availability, forecasting, replenishment, supply chain efficiency, workforce effectiveness, operational productivity, customer experience, and decision-making.
  • Drive the development and productionization of GenAI solutions, including enterprise copilots, intelligent assistants, RAG-based applications, agentic AI workflows, natural-language analytics, and knowledge-driven automation.
  • Establish standards for LLM evaluation, grounding, guardrails, responsible AI, security, observability, model monitoring, and human-in-the-loop controls.
  • Partner with Data Engineering, Architecture, and Platform teams to establish scalable MLOps and LLMOps capabilities using GCP, Vertex AI, and enterprise data platforms.
  • Lead advanced Data Science capabilities including forecasting, optimization, recommendation systems, predictive modeling, experimentation, segmentation, anomaly detection, and simulation/What-If modeling.
  • Ensure AI/ML solutions are built with production-grade engineering standards, including scalability, reliability, monitoring, data quality, automated testing, reproducibility, and lifecycle management.
  • Establish measurable KPIs and ROI frameworks that connect model performance to business outcomes and financial value.
  • Translate complex model outputs and AI capabilities into actionable recommendations and compelling narratives for executive and business leadership.
  • Build strong partnerships with senior leaders across Inventory, Supply Chain, Store Operations, HR/People Analytics, Merchandising, Digital, and Technology.
  • Lead portfolio prioritization based on business value, feasibility, strategic alignment, and implementation effort.
  • Develop Data Science leaders and individual contributors through coaching, technical mentorship, career development, and succession planning.
  • Stay ahead of emerging developments in Generative AI, Agentic AI, Machine Learning, optimization, and retail technology, and determine where they can create meaningful enterprise value.
  • Own resource planning, vendor strategy, budget management, delivery risks, and execution across the Data Science and Applied AI portfolio.

Required Skills:
  • Proven leadership experience managing Data Science, Machine Learning, or Applied AI teams, preferably across multiple business domains.
  • Strong expertise in Machine Learning, Applied AI, Generative AI, optimization, predictive modeling, and advanced analytics.
  • Hands-on understanding of modern GenAI architectures, including LLMs, RAG, embeddings/vector search, AI agents, prompt engineering, model evaluation, guardrails, and LLMOps.
  • Strong experience with enterprise cloud AI platforms, preferably GCP and Vertex AI.
  • Experience designing and operationalizing scalable MLOps/LLMOps architectures and production AI solutions.
  • Demonstrated ability to connect AI/ML initiatives to measurable operational and financial outcomes.
  • Strong understanding of data engineering, data quality, governance, security, and enterprise data architecture required to support AI at scale.
  • Proven ability to influence senior executives and translate ambiguous business challenges into a prioritized portfolio of Data Science and AI initiatives.
  • Strong people leadership experience, including hiring, developing, coaching, and retaining Data Science and AI talent.
  • Excellent executive communication, storytelling, stakeholder management, and organizational leadership skills.

Preferred:
  • Retail industry experience, particularly within large-scale, multi-channel or store-based retail environments.
  • Deep business understanding of Inventory Management, Inventory Optimization, Demand Forecasting, Replenishment, Supply Chain, Distribution, and Store Operations.
  • Experience applying AI/ML to retail use cases such as demand forecasting, inventory optimization, assortment, pricing, workforce optimization, customer personalization, and operational decision-making.
  • Experience leading People Analytics/Data Science initiatives such as workforce planning, retention, engagement, labor optimization, and talent analytics.
  • Experience delivering Generative AI and Agentic AI solutions from experimentation through production.
  • Experience driving organizational adoption and change management around AI-enabled ways of working.
  • Experience partnering with Product, Engineering, Data, and Business organizations to move AI solutions from POC to production and measurable business value.

Education: Master's Degree or Equivalent Level
Experience: Wide and deep experience providing expert competence (Over 10 years to 15 years)
Managerial Experience: Experience of planning and managing resources to deliver predetermined objectives as specified by more senior managers (Over 3 years to 6 years)
O'Reilly Auto Parts has a proven track record of growth and stability. O'Reilly is full of successful career stories and believes in a strong promote-from-within philosophy, encouraging you to grow your career along with the organization.
Total Compensation Package:
  • Competitive Wages & Paid Time Off
  • Stock Purchase Plan & 401k with Employer Contributions Starting Day One
  • Medical, Dental, & Vision Insurance with Optional Flexible Spending Account (FSA)
  • Team Member Health/Wellbeing Programs
  • Tuition Educational Assistance Programs
  • Opportunities for Career Growth

O'Reilly Auto Parts is an equal opportunity employer. The Company does not discriminate on the basis of race, religion, color, national origin or ancestry (including immigration status or citizenship), sex, sexual orientation, gender identity, pregnancy (including childbirth, lactation, and related medical conditions,) age (40 and over), veteran status, uniformed service member status, physical or mental disability, genetic information (including testing or characteristics) or another protected status as defined by local, state, or federal law, as applicable.
Qualified individuals with a disability may be entitled to reasonable accommodation under the Americans with Disabilities Act. If you require a reasonable accommodation during the application or employment process, please send an email to: rar@oreillyauto.com or call (800) 471-7431 option , and provide your requested accommodation, and position details.

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