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Data Science Phd information

What is a data science PhD?

A Data Science PhD is a doctoral-level degree focused on advanced research in data science, which combines elements of statistics, computer science, and domain expertise. Students in a Data Science PhD program typically work on developing new methods for analyzing large datasets, creating machine learning algorithms, and addressing complex problems in areas such as artificial intelligence, data mining, and predictive analytics. Graduates are prepared for careers in academia, research, and industry, where they can lead data-driven projects and contribute to advancements in the field.

What are the key skills and qualifications needed to thrive as a data science PhD?

To thrive as a Data Science PhD, you need advanced expertise in statistics, machine learning, data analysis, and a doctoral degree in a quantitative field. Proficiency in programming languages like Python or R, experience with big data frameworks (e.g., Spark, Hadoop), and familiarity with data visualization tools are typically required. Critical thinking, problem-solving, and strong communication skills help you translate complex data insights for diverse stakeholders. These skills are vital for driving innovative research, making data-driven decisions, and contributing impactful solutions in data-centric environments.

What are some common challenges faced by data science PhDs when transitioning from academia to industry roles?

Data Science PhDs often encounter challenges such as adapting to the faster pace and collaborative nature of industry projects compared to academic research. In industry, there is a greater emphasis on delivering practical solutions within tight deadlines and working closely with cross-functional teams like engineering and product management. Additionally, data science work in industry may require balancing technical rigor with business impact, often prioritizing actionable insights over exhaustive analysis. Building strong communication and stakeholder management skills can help ease this transition.

What can I do with a data science PhD?

A data science PhD prepares individuals for advanced roles in research, analytics, and machine learning across industries such as technology, finance, healthcare, and academia. Graduates can work as data scientists, machine learning engineers, research scientists, or data analysts, often utilizing programming languages like Python or R and tools such as TensorFlow or SQL. The degree also enables roles involving complex data modeling, statistical analysis, and developing innovative data-driven solutions.

What are popular job titles related to Data Science Phd jobs in Oklahoma?

For Data Science Phd jobs in Oklahoma, the most frequently searched job titles are:

What job categories do people searching Data Science Phd jobs in Oklahoma look for?

The top searched job categories for Data Science Phd jobs in Oklahoma are:

What cities in Oklahoma are hiring for Data Science Phd jobs?

Cities in Oklahoma with the most Data Science Phd job openings:

Data Science Phd jobs near you
Infographic showing various Data Science Phd job openings in Oklahoma as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 14% Part Time, and 4% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution.

Sr. Manager of Analytics and Data Science

Love's Travel Stops and Country Stores

Oklahoma City, OK • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 18 days ago

Love's Travel Stops rating

5.9

Company rating: 5.9 out of 10

Based on 801 frontline employees who took The Breakroom Quiz

405th of 739 rated retailers

Job description

Benefits: * Fuel Your Growth with Love's - company funded tuition assistance * Paid Time Off * 401(k) – 100% Match up to 5% * Medical/Dental/Vision Insurance the first of the month after 30 days * Competitive Pay * Career Development *  

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. 

Job Functions: 

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 

Experience and Qualifications:

  • 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

Skills and Physical Demands: 

  • 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

Our Culture: 

Fueling customers' journeys since 1964, innovation leads the way for this family-owned and operated business headquartered in Oklahoma City. With nearly 40,000 team members, travel stops are the core business along with products and services that provide value for professional drivers, fleets, traveling public, RVers, alternative energy and wholesale fuel customers. Giving back to communities and an inclusive workplace are hallmarks of the award-winning culture.

Love's is an Equal Opportunity Employer. Veterans encouraged to apply.

What Love's Travel Stops employees say

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