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Machine Learning Manager Jobs in Tulsa, OK (NOW HIRING)

SageNet LLC

AI Engineer

Tulsa, OK · On-site

S., SageNet connects, manages, and protects technologies and devices across widely distributed ... Research and evaluate emerging AI technologies, including generative AI and machine learning ...

SageNet

AI Engineer

Tulsa, OK · On-site

S., SageNet connects, manages, and protects technologies and devices across widely distributed ... Research and evaluate emerging AI technologies, including generative AI and machine learning ...

Deloitte

Finance Analytics & AI Manager

Tulsa, OK · On-site

One or more certifications in artificial intelligence, machine learning, Amazon Web Services ... Our Managers are expected to contribute to the firm's growth and development in a variety of ways.

Deloitte

Finance Analytics & AI Manager

Tulsa, OK

One or more certifications in artificial intelligence, machine learning, Amazon Web Services ... Our Managers are expected to contribute to the firm's growth and development in a variety of ways.

Deloitte

Kinaxis Manager

Tulsa, OK · On-site

We modernize supply chains by implementing artificial intelligence, machine learning, and connected ... This role will manage solution delivery through a variety of activities including process design ...

Staffmark Group

Machinist

Tulsa, OK · On-site

$21/hr

Good management, good people to work with, clean facility." - Machinist, Staffmark Ready to put your machining skills to work? Join a team that values precision, safety, and continuous learning.

New

Varsity Tutors

Business Analytics Tutor

Tulsa, OK · Remote

$18 - $40/hr

Ability to explain statistical modeling techniques, machine learning basics, and business intelligence dashboard design while preparing students for analytics roles and data-driven management ...

Deloitte

Microsoft D365 F&O SCM Manager

Tulsa, OK

We modernize their supply chains using artificial intelligence, machine learning and connected ... Experience with D365 Manufacturing, advanced Warehouse Management * Familiarity with key ISV ...

Pwc

ERP AI Engineer - Manager

Tulsa, OK · On-site

$99K - $232K/yr

Industry/Sector Not Applicable Specialism Oracle Management Level Manager & Summary At PwC, our ... Machine Learning. Enhancing your leadership style, you motivate, develop and inspire others to ...

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All JobsMachine Learning JobsMachine Learning Manager JobsMachine Learning Manager Jobs in Tulsa, OK

Machine Learning Manager information

See Tulsa, OK salary details

$46.6K

$74.6K

$107.8K

How much do machine learning manager jobs pay per year?

As of Jul 13, 2026, the average yearly pay for machine learning manager in Tulsa, OK is $74,630.00, according to ZipRecruiter salary data. Most workers in this role earn between $60,300.00 and $84,500.00 per year, depending on experience, location, and employer.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and maintain AI systems, and their role involves understanding algorithms, data processing, and model deployment. While AI automation tools can handle certain tasks, MLEs are essential for creating, optimizing, and overseeing complex AI solutions, making complete replacement unlikely in the near term.

What are some of the main challenges a Machine Learning Manager faces when leading a team?

A Machine Learning Manager often navigates challenges such as balancing project deadlines with the need for thorough experimentation and research, ensuring clear communication between technical and non-technical stakeholders, and fostering collaboration among data scientists, engineers, and product teams. Additionally, managers must keep their team's skills current with rapidly evolving technologies while also addressing issues like data quality and model deployment in production environments. Successfully overcoming these challenges requires strong leadership, adaptability, and a deep understanding of both business objectives and technical intricacies.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior machine learning manager or director, often involving leadership, advanced technical skills, and strategic responsibilities. These roles usually require extensive experience, expertise in AI tools and frameworks, and may include performance-based bonuses or stock options that contribute to the total compensation. Such salaries are common in large tech companies or organizations with significant AI investments.

What are the key skills and qualifications needed to thrive as a Machine Learning Manager, and why are they important?

To thrive as a Machine Learning Manager, you need a robust background in machine learning algorithms, statistical analysis, and software engineering, typically supported by an advanced degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and project management platforms, along with experience in deploying ML systems, is essential. Strong leadership, communication, and strategic thinking skills set exceptional managers apart, enabling them to guide teams and align projects with business objectives. These skills are crucial to successfully leading technical teams, ensuring project delivery, and translating complex ML solutions into organizational value.

Is ML a high paying job?

Machine Learning Managers typically earn high salaries due to the specialized skills required, such as expertise in algorithms, programming, and data analysis. Compensation varies based on experience, location, and industry, but it is generally above average compared to many other tech roles.

Which 3 jobs will survive AI?

Machine Learning Managers will continue to be essential as they oversee AI projects, interpret complex data, and coordinate teams, tasks that require strategic thinking and human judgment. Roles that involve creative problem-solving, emotional intelligence, and domain-specific expertise, such as healthcare professionals, educators, and skilled tradespeople, are also likely to persist despite AI advancements. These jobs rely on human intuition and adaptability that AI cannot fully replicate.

What are Machine Learning Managers?

Machine Learning Managers are professionals responsible for leading teams that develop, implement, and maintain machine learning models and systems. They oversee data scientists, engineers, and other specialists, ensuring projects align with business goals and are delivered on time. Their role often involves coordinating cross-functional teams, managing project timelines, and staying current with the latest advancements in artificial intelligence and machine learning. Additionally, they may be involved in hiring, mentoring, and providing technical guidance to their team.
What are the most commonly searched types of Machine Learning jobs in Tulsa, OK? The most popular types of Machine Learning jobs in Tulsa, OK are:
What are popular job titles related to Machine Learning Manager jobs in Tulsa, OK? For Machine Learning Manager jobs in Tulsa, OK, the most frequently searched job titles are:
What job categories do people searching Machine Learning Manager jobs in Tulsa, OK look for? The top searched job categories for Machine Learning Manager jobs in Tulsa, OK are:
Machine Learning Manager jobs near you
Infographic showing various Machine Learning Manager job openings in Tulsa, OK as of July 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, 1% Temporary, and 1% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $74,630 per year, or $35.9 per hour.
Manager, Outcomes and Performance Analysis

Manager, Outcomes and Performance Analysis

Family & Children's Services

Tulsa, OK

Full-time

Posted 11 days ago

Job description

job summary:

The Manager, Outcomes & Performance Analytics supports the organization’s ability to understand whether strategic initiatives, operational improvements, and analytics are achieving measurable results.

This role evaluates initiative performance by analyzing outcomes against established goals, success criteria, baseline measures, and expected value. The Manager identifies what outcomes were achieved, what outcomes were not achieved, and the factors influencing results.

The Manager translates analytical findings into actionable insights and presents evaluation results, performance trends, and recommendations to leadership teams and executive stakeholders to support informed decision-making.

POSITION SPECIFIC DUTIES & RESPONSIBILITIES:    

Outcomes & Performance Measurement

  • Analyze organizational initiatives, programs, and operational improvements to determine effectiveness and impact
  • Measure changes in quality, efficiency, productivity, utilization, cost, and performance
  • Compare expected outcomes against actual results
  • Identify trends, gaps, and factors influencing performance
  • Develop recurring outcome summaries, performance reports, and impact assessments

 Initiative Evaluation & Impact Analysis

  • Evaluate analytics, AI, technology, process improvement, and operational initiatives using established evaluation methods
  • Assess whether initiatives achieved intended outcomes and measurable benefits
  • Analyze sustainability of improvements over time
  • Identify opportunities to improve effectiveness, adoption, and value realization
  • Document evaluation findings, lessons learned, and improvement opportunities

Value Realization & ROI Analysis

  • Support measurement of business value, including:
    • Efficiency improvements
    • Productivity gains
    • Cost savings
    • Quality improvements
    • Operational benefits
  • Analyze whether investments and initiatives achieved expected value
  • Prepare value realization summaries for leadership review
  • Provide objective findings to support discussions regarding continuation, modification, or scaling of initiatives

 Adoption & Utilization Analysis

  • Monitor adoption and utilization of dashboards, reports, self-service analytics, and AI-enabled solutions
  • Analyze usage patterns and identify barriers impacting successful adoption
  • Evaluate the relationship between adoption and realized outcomes
  • Provide recommendations to improve utilization and organizational impact

  Executive Reporting & Data Storytelling

  • Develop executive ready reports, presentations, scorecards, and briefing materials
  • Present outcome analyses and evaluation findings to leadership teams and executive stakeholders
  • Communicate complex analytical findings in a clear, concise, and meaningful manner
  • Provide objective insights focused on:
    • What worked
    • What did not work
    • What value was created
    • What factors influenced outcomes
    • What opportunities exist for improvement
  • Respond to leadership questions regarding analysis, evaluation methods, and findings

 CQI & Continuous Improvement Collaboration

  • Partner with CQI and operational teams to evaluate improvement initiatives
  • Support pilots, phased implementations, and post-implementation reviews
  • Analyze effectiveness, sustainability, and measurable impact of improvement efforts
  • Identify interventions and practices associated with improved outcomes
  • Support organizational learning through evidence-based evaluation

Cross-Functional Analytics Partnership

  • Collaborate with BI, Machine Learning, Data Engineering, Finance, PMO, CQI, and operational teams
  • Leverage available data assets to conduct meaningful evaluations
  • Provide outcomes and performance perspectives during initiative reviews
  • Support consistent approaches for measuring impact across the organization

Leadership Responsibilities

  • Manage assigned outcomes evaluation and performance analytics activities
  • Serve as a subject matter resource for outcomes measurement and performance evaluation
  • Present findings and insights to leadership and executive stakeholders
  • Influence cross-functional partners through objective analysis and evidence-based insights
  • Promote accountability for measurable outcomes and value realization
  • Support consistent evaluation practices across departments

Key Deliverables

  • Outcome Performance Reports
  • Initiative Evaluation Summaries
  • ROI and Value Realization Assessments
  • Adoption and Utilization Analysis Reports
  • Executive Outcome Presentations
  • Performance Scorecards
  • Post-Implementation Review Summaries
  • Leadership Briefing Materials
  • Evidence-Based Recommendations

QUALIFICATIONS

education:

  • Bachelor's Degree in related field is required
  • Master's degree preferred

EXPERIENCE:

  • 5+ years of experience in analytics, evaluation, business intelligence, performance improvement, research, strategy, or related fields
  • Experience analyzing organizational outcomes, program effectiveness, or operational performance
  • Experience developing reports and presentations for leadership audiences
  • Experience translating data into actionable insights and recommendations
  • Healthcare, behavioral health, nonprofit, or human services experience preferred

PERFORMANCE COMPETENCIES: 

  • Communication
  • Decision Making
  • Engagement
  • Initiative and Accountability
  • Interpersonal
  • Learning
  • Organizational Alignment
  • Quality of Work

KNOWLEDGE/SKILLS/ABILITIES:

  • Strong analytical and critical-thinking skills
  • Experience with business intelligence and reporting tools
  • Knowledge of evaluation methodologies, performance measurement, or CQI practices
  • Strong data storytelling and presentation skills
  • Ability to communicate complex findings to technical and non-technical audiences
  • Ability to collaborate effectively across departments and organizational levels
  • Ability to influence stakeholders through evidence and analysis

CERTIFICATIONS/LICENSES:

  • Must possess a valid Driver License and satisfactory driving record to use agency and/or personal automobile to travel to locations other than primary office.

OTHER INFORMATION

SAFETY SENSITIVE JOB CLASSIFICATION:

This job is classified as a “safety-sensitive” position as defined by the Oklahoma Medical Marijuana and Patient Protection Act.  Due to the “safety-sensitive” classification, an employee in this position would be subject to drug and alcohol testing, including random testing.  Marijuana is one of the substances included in the drug panel screening.  Possession of a medical marijuana license will not excuse you from the testing process or the consequences of testing positive for marijuana per the Family & Children’s Services Drug Free Workplace Policy, including possible revocation of a job offer or dismissal from employment.

 

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