Manager - Data Science

Expand Energy

Oklahoma City (OK)

On-site

USD 140,000 - 200,000

Full time

48 hours ago
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Job summary

Expand Energy is seeking a Data Science Manager to lead the Data Science team and serve as the primary delivery leader within the Fusion Team operating model. This role converts business opportunities into production-grade AI, ML, and analytics solutions delivering enterprise value.

The manager leads a multidisciplinary team while partnering with stakeholders, Digital Advancement, IT, and the AI Platform organization.

Qualifications

  • Experience delivering production AI/ML solutions in a business environment.
  • Strong data engineering and ML lifecycle management knowledge.
  • Proven track record leading cross-functional data projects.
  • Excellent communication with stakeholders and leadership.
  • Ability to balance strategic priorities with day-to-day execution.

Responsibilities

  • Lead delivery of AI/ML and analytics initiatives from concept to production.
  • Maintain a prioritized backlog aligned to business objectives.
  • Oversee cross-functional delivery across multiple domains and teams.
  • Ensure governance, testing, and mloPs practices are followed.
  • Mentor data scientists and data engineers for growth and performance.
  • Collaborate with business leaders to realize measurable value.

Skills

AI/ML delivery
Data engineering
Leadership
Stakeholder management
Execution excellence

Education

Bachelor's degree in Data Science or related field

Job description

Our core values — Stewardship, Character, Collaborate, Learn, Disrupt — are the lens through which we evaluate every business decision. As a dynamic, growing company that offers extremely competitive compensation and benefits, our employees are our most valued assets and the foundation of Expand's performance among our E&P competitors.

We seek applicants from all backgrounds to ensure we get the best, most creative talent on our team. We realize that, historically, underrepresented groups feel the need to be 100% qualified in order to apply. If you meet any combination of our requirements, we encourage you to apply. We strive to hire people from a wide variety of backgrounds, not just because it’s the right thing to do, but because it makes our company stronger.

Job Summary

Expand Energy is seeking a Data Science Manager to lead the Data Science team and serve as the primary delivery leader within the Fusion Team operating model. This role converts business opportunities into production-grade AI, machine learning, and advanced analytics solutions that deliver measurable enterprise value. The manager leads a multidisciplinary team while partnering closely with business stakeholders, Digital Advancement, IT, and the AI Platform organization.

Job Duties & Responsibilities
Delivery Leadership & Execution
  • Lead the delivery of AI, machine learning, and advanced analytics initiatives from concept through production deployment
  • Own and maintain a prioritized backlog aligned to business objectives and enterprise AI priorities
  • Facilitate planning, work prioritization, sprint execution, reviews, and retrospectives
  • Manage resource allocation and delivery capacity across multiple business domains and competing priorities
  • Maintain visibility into project status, milestones, dependencies, risks, and issues
  • Proactively remove obstacles and coordinate cross-functional teams to ensure predictable delivery
Technical Leadership & Model Lifecycle Management
  • Ensure AI, machine learning, and analytics solutions adhere to established development, testing, deployment, and governance standards
  • Promote disciplined software engineering and MLOps practices, including source control, peer review, testing, and deployment controls
  • Champion reproducibility, model quality, and operational excellence across delivered solutions
  • Partner with technical leads and architects on solution design while avoiding becoming a bottleneck for technical decisions
  • Oversee model performance after deployment and drive remediation for drift, degradation, or technical debt
Business Value Realization
  • Partner with business leaders to translate strategic opportunities into practical AI and analytics solutions
  • Ensure initiatives are aligned to measurable business outcomes and expected value realization
  • Manage stakeholder expectations, scope, priorities, and delivery commitments
  • Ensure technical solutions are documented, maintainable, and positioned for sustainable business adoption
  • Contribute delivery metrics and performance insights that support leadership reporting and value measurement
Governance, Risk & Responsible AI
  • Ensure data usage and model development comply with company policies and governance requirements
  • Embed responsible AI practices, model transparency, and documentation standards into day-to-day delivery
  • Identify and elevate risks related to model performance, data quality, security, compliance, and ethical AI considerations
  • Promote governance as an integrated part of delivery rather than a downstream approval activity
People Leadership & Talent Development
  • Lead, coach, and develop a team of data scientists and data engineers
  • Create opportunities for mentorship, technical growth, and cross-functional learning
  • Foster an environment of collaboration, innovation, ownership, and continuous learning
Cross-Functional Leadership & Enterprise Collaboration
  • Lead Fusion Teams consisting of business stakeholders, Digital Advancement resources, and IT partners
  • Drive alignment across technical and business teams through shared goals, priorities, and accountability
  • Collaborate with enterprise platform teams on infrastructure, data architecture, and reusable capabilities
  • Promote knowledge sharing, best practices, and enterprise-wide adoption of proven AI and analytics patterns
  • Coordinate effectively with external vendors, implementation partners, and consulting resources when needed
Job Specific Skills
  • Experience delivering production AI/ML solutions and data products in a business environment, required
  • Strong understanding of data engineering, machine learning lifecycle management, and software development practices, required
  • Experience leading cross-functional projects involving business stakeholders, technology teams, and external partners, required
  • Strong communication, stakeholder management, and organizational leadership skills, required
  • Demonstrated ability to balance strategic priorities with day-to-day execution, required
Education

Minimum: Bachelor’s degree - from accredited university - Data Science, Computer Science, Engineering, Statistics, Mathematics, or related field

Experience

Minimum: 8 years related work experience in data science, machine learning, analytics, or related disciplines

3+ years of experience leading technical teams and managing direct reports

Additional Qualifications
  • Advanced degree in Data Science, Computer Science, Statistics, Engineering, or related discipline, preferred
  • Experience with Azure, Snowflake, Git-based development workflows, DevOps pipelines, and modern MLOps practices, preferred
  • Experience operating in an Agile delivery environment, preferred
  • Oil and gas industry experience or experience supporting complex industrial operations, preferred
  • Experience building and scaling AI products from pilot through enterprise deployment, preferred

Expand Energy takes necessary action to ensure that all applicants are treated without regard to their race, color, religion, sex, sexual orientation, age, gender identity, national origin, genetic information, disability, pregnancy, military or veteran status or any other protected characteristic as established by law.

Expand Energy Corporation's operations are focused on discovering and developing its large and geographically diverse resource base of unconventional oil and natural gas assets onshore in the United States.

Nearest Major Market: Oklahoma City

Nearest Secondary Market: Oklahoma

Job Segment: Computer Science, Test Engineer, Data Management, Testing, Sustainability, Technology, Engineering, Data, Energy

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