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Contract Machine Learning Data Scientist Jobs in Oklahoma

Deloitte

Lead AI and Data Science Engineer II

Tulsa, OK · On-site

$93K - $123K/yr

In this role, you will lead complex data science work that combines research design, statistical analysis, machine learning, and application development to solve high-priority people challenges. You ...

Deloitte

Finance Analytics & AI Senior Consultant

Tulsa, OK · On-site

$106K/yr

Master's degree in Computer Science, Data Science, Analytics, Finance, Mathematics, or Statistics * Experience deploying machine learning or generative and agentic AI solutions into production ...

mytfcuhr

Data Engineer I,II,III, SR

Oklahoma City, OK · On-site

$106K - $133K/yr

A master's degree in computer science, information systems, computer engineering, artificial intelligence, machine learning, data science, or a closely related field is preferred at the Senior level.

Accenture

$94K - $293K/yr

Minimum of 6 years of extensive full-time experience in Data Analysis, Statistics, Machine Learning ... Computer Science * Minimum of 5 years of experience in machine learning, deep learning, or ...

Strayos

$13 - $17.50/hr

Here at Strayos, we use advanced computer vision and machine learning on images and machine sensors data to build insights for Mining, Infrastructure and Construction industry. Our applied science ...

Bespoke Labs

Machine Learning Engineer

Tulsa, OK · On-site

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

Bespoke Labs

Machine Learning Engineer

Lawton, OK · On-site

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

Bespoke Labs

Machine Learning Engineer

Norman, OK · On-site

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

Bespoke Labs

Machine Learning Engineer

Edmond, OK · On-site

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

Expand Energy

Data Architect

Oklahoma City, OK · On-site

$52.25 - $67.25/hr

Support teams in operationalizing machine learning solutions at scale Emerging Capabilities ... Bachelor's degree in Information Systems, Computer Science, or related field Experience Minimum: 8 ...

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All JobsContract Machine Learning Data Scientist JobsContract Machine Learning Data Scientist Jobs in Oklahoma

Contract Machine Learning Data Scientist information

How do contract machine learning data scientists typically collaborate with in-house teams during a project?

Contract machine learning data scientists often work closely with in-house data teams, product managers, and engineers to align project goals and deliverables. They frequently participate in virtual meetings, code reviews, and regular progress updates to ensure transparency and seamless integration of their work. Effective communication and documentation are critical, as contractors may need to quickly adapt to the company's workflows and tools. This collaborative environment enables contractors to contribute specialized expertise while staying attuned to the broader objectives of the organization.

What are the key skills and qualifications needed to thrive as a contract machine learning data scientist?

To excel as a Contract Machine Learning Data Scientist, you need a strong background in statistics, programming (Python/R), and applied machine learning, typically supported by a relevant degree in computer science, mathematics, or a related field. Familiarity with tools and frameworks such as TensorFlow, PyTorch, scikit-learn, cloud platforms (AWS, GCP, Azure), and version control systems is essential, along with experience deploying models in production. Exceptional problem-solving abilities, communication skills, and adaptability help you translate business needs into actionable data solutions and quickly integrate into new teams. These skills are crucial for delivering high-impact, reliable machine learning solutions on tight project timelines and in diverse organizational environments.

What is the difference between Contract Machine Learning Data Scientist vs Contract Data Scientist?

AspectContract Machine Learning Data ScientistContract Data Scientist
CredentialsTypically requires advanced degrees in data science, machine learning, or related fieldsRequires similar degrees but may have a broader focus on data analysis
Work EnvironmentOften in tech, finance, or healthcare industries focusing on ML projectsVaries across industries, including marketing, finance, and consulting
Employer UsageUsed by companies developing AI/ML solutions or productsEmployed for data analysis, reporting, and strategic insights
Search & Comparison IntentOften searched by those interested in AI/ML-specific rolesMore general, related to data analysis roles

The main difference is that Contract Machine Learning Data Scientists focus on developing and implementing machine learning models, while Contract Data Scientists may handle broader data analysis tasks without necessarily specializing in ML. Both roles require strong analytical skills and relevant credentials, but their project focus and industry applications differ.

What is a contract machine learning data scientist?

A Contract Machine Learning Data Scientist is a professional who works on a temporary or project-based basis to build, implement, and optimize machine learning models for organizations. Unlike full-time employees, contract data scientists are hired for specific projects or timeframes and may work independently or as part of a team. Their responsibilities typically include data cleaning, feature engineering, model selection, and communicating insights to stakeholders. Contract roles offer flexibility for both the professional and the employer, often focusing on specialized tasks or filling short-term skill gaps.

What are popular job titles related to Contract Machine Learning Data Scientist jobs in Oklahoma?

For Contract Machine Learning Data Scientist jobs in Oklahoma, the most frequently searched job titles are:

What job categories do people searching Contract Machine Learning Data Scientist jobs in Oklahoma look for?

The top searched job categories for Contract Machine Learning Data Scientist jobs in Oklahoma are:

What cities in Oklahoma are hiring for Contract Machine Learning Data Scientist jobs?

Cities in Oklahoma with the most Contract Machine Learning Data Scientist job openings:

Contract Machine Learning Data Scientist jobs near you

Lead AI and Data Science Engineer II

Deloitte

Tulsa, OK • On-site

$93K - $123K/yr

Full-time

Posted 17 days ago

Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

44th of 150 rated financial services

Job description

Lead AI and Data Science Engineer II

Drive the design and delivery of advanced analytics, artificial intelligence (AI), and generative artificial intelligence (GenAI) solutions that inform Talent strategy and workforce decisions. In this role, you will lead complex data science work that combines research design, statistical analysis, machine learning, and application development to solve high-priority people challenges. You will also partner with business, Talent, and technology stakeholders to translate workforce data into actionable insights, tools, and recommendations.

Recruiting for this role ends on August 10, 2026.

Work You'll Do

In this role, you will lead the data science dimension of that work, shaping research design, analytical methodology, and solution development while helping develop junior data scientists across the full analytics lifecycle.

Strategy & Stakeholder Partnership

  • Partner with the Advanced Analytics & AI leader to help shape and execute the People Analytics portfolio, using data-driven insights to inform Talent strategy, establish priorities, and manage multiple initiatives.
  • Collaborate with stakeholders across Talent, business leadership, and ITS to define business needs, identify analytics opportunities, communicate complex technical concepts, and advise on the benefits and limitations of automation and artificial intelligence (AI).
  • Develop and drive strategy to understand and improve data quality across relevant Talent data assets.

Analytics & Data Science

  • Design and structure analytical work, including research design, project planning, and use case development, and apply advanced statistical and machine learning methods to generate rigorous, actionable insights.
  • Perform analytics in cloud-based environments, support the development of clear leadership-ready presentations, and stay current on developments in data science, behavioral science, and adjacent disciplines.

Software & Data Engineering

  • Develop full-stack, web-based data and generative artificial intelligence (GenAI) applications that improve Talent reporting and business operations.
  • Partner with data engineering teams on pipeline architecture and infrastructure, using knowledge of extract, transform, load (ETL), version control, and continuous integration and continuous delivery (CI/CD) concepts to inform technical decisions.

People Leadership

  • Mentor junior and mid-level data scientists across the analytics lifecycle, from problem framing and data collection through analysis and synthesis of findings.
  • Provide structure and oversight for analytically complex projects, while assessing talent, delivering developmental feedback, and contributing to a high-performing analytics team.

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to mentor and provide clear guidance to others

The team

The Talent Experience & Engagement, People Analytics - Advanced Analytics & AI team helps the firm make informed people and business decisions by translating workforce data into actionable insights, tools, and strategies. The team combines behavioral science, organizational research, advanced analytics, and artificial intelligence (AI) to address leadership questions, improve decision-making, and create scalable solutions with measurable impact.

The work is delivered through two connected capabilities. Organizational research and storytelling ground analyses in rigorous social science and clear, decision-oriented narratives. Data science applies statistical analysis, machine learning, and AI to identify meaningful patterns in workforce data, build data and generative artificial intelligence (GenAI) applications, and partner with Talent data engineering teams on pipelines and infrastructure.

Qualifications

Required:

  • Graduate degree in Applied Statistics, Computer Science, Life Sciences, Industrial-Organizational Psychology, Organizational Behavior, Sociology, Economics, Anthropology, or another quantitative discipline
  • 6+ years of experience in data science, analytics, or applied research
  • Experience using Python and Structured Query Language (SQL), with working knowledge of JavaScript, TypeScript, HyperText Markup Language (HTML), and Cascading Style Sheets (CSS)
  • Experience applying multivariate statistics and machine learning methods, including regression, structural equation modeling, factor analysis, decision trees, clustering, and dimension reduction, in Apache Spark or Databricks environments
  • Experience developing artificial intelligence (AI) or generative artificial intelligence (GenAI) applications and working with extract, transform, load (ETL), pipeline design, and orchestration concepts
  • Demonstrated experience leading AI strategy and enabling adoption of AI or data engineering tools within a complex organizational environment
  • Mentorship of junior and mid-level analysts, providing guidance across the analytics lifecycle from conception through data mining/analysis and synthesis of results
  • Ability to travel 0-10%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.

Preferred:

  • Doctor of Philosophy (PhD) in Applied Statistics, Computer Science, Life Sciences, Industrial-Organizational Psychology, Organizational Behavior, Sociology, Economics, Anthropology, or another quantitative discipline
  • Experience in a professional services organization or large matrixed organization
  • Experience designing and building end-to-end data pipelines for reporting and analytics
  • Experience applying behavioral science frameworks to interpret workforce data and generate insight - not solely technical or statistical proficiency
  • Experience with talent systems such as OneModel or SAP

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $118700 to $218600.

Qualifications:

Lead AI and Data Science Engineer II

Drive the design and delivery of advanced analytics, artificial intelligence (AI), and generative artificial intelligence (GenAI) solutions that inform Talent strategy and workforce decisions. In this role, you will lead complex data science work that combines research design, statistical analysis, machine learning, and application development to solve high-priority people challenges. You will also partner with business, Talent, and technology stakeholders to translate workforce data into actionable insights, tools, and recommendations.

Recruiting for this role ends on August 10, 2026.

Work You'll Do

In this role, you will lead the data science dimension of that work, shaping research design, analytical methodology, and solution development while helping develop junior data scientists across the full analytics lifecycle.

Strategy & Stakeholder Partnership

  • Partner with the Advanced Analytics & AI leader to help shape and execute the People Analytics portfolio, using data-driven insights to inform Talent strategy, establish priorities, and manage multiple initiatives.
  • Collaborate with stakeholders across Talent, business leadership, and ITS to define business needs, identify analytics opportunities, communicate complex technical concepts, and advise on the benefits and limitations of automation and artificial intelligence (AI).
  • Develop and drive strategy to understand and improve data quality across relevant Talent data assets.

Analytics & Data Science

  • Design and structure analytical work, including research design, project planning, and use case development, and apply advanced statistical and machine learning methods to generate rigorous, actionable insights.
  • Perform analytics in cloud-based environments, support the development of clear leadership-ready presentations, and stay current on developments in data science, behavioral science, and adjacent disciplines.

Software & Data Engineering

  • Develop full-stack, web-based data and generative artificial intelligence (GenAI) applications that improve Talent reporting and business operations.
  • Partner with data engineering teams on pipeline architecture and infrastructure, using knowledge of extract, transform, load (ETL), version control, and continuous integration and continuous delivery (CI/CD) concepts to inform technical decisions.

People Leadership

  • Mentor junior and mid-level data scientists across the analytics lifecycle, from problem framing and data collection through analysis and synthesis of findings.
  • Provide structure and oversight for analytically complex projects, while assessing talent, delivering developmental feedback, and contributing to a high-performing analytics team.

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to mentor and provide clear guidance to others

The team

The Talent Experience & Engagement, People Analytics - Advanced Analytics & AI team helps the firm make informed people and business decisions by translating workforce data into actionable insights, tools, and strategies. The team combines behavioral science, organizational research, advanced analytics, and artificial intelligence (AI) to address leadership questions, improve decision-making, and create scalable solutions with measurable impact.

The work is delivered through two connected capabilities. Organizational research and storytelling ground analyses in rigorous social science and clear, decision-oriented narratives. Data science applies statistical analysis, machine learning, and AI to identify meaningful patterns in workforce data, build data and generative artificial intelligence (GenAI) applications, and partner with Talent data engineering teams on pipelines and infrastructure.

Qualifications

Required:

  • Graduate degree in Applied Statistics, Computer Science, Life Sciences, Industrial-Organizational Psychology, Organizational Behavior, Sociology, Economics, Anthropology, or another quantitative discipline
  • 6+ years of experience in data science, analytics, or applied research
  • Experience using Python and Structured Query Language (SQL), with working knowledge of JavaScript, TypeScript, HyperText Markup Language (HTML), and Cascading Style Sheets (CSS)
  • Experience applying multivariate statistics and machine learning methods, including regression, structural equation modeling, factor analysis, decision trees, clustering, and dimension reduction, in Apache Spark or Databricks environments
  • Experience developing artificial intelligence (AI) or generative artificial intelligence (GenAI) applications and working with extract, transform, load (ETL), pipeline design, and orchestration concepts
  • Demonstrated experience leading AI strategy and enabling adoption of AI or data engineering tools within a complex organizational environment
  • Mentorship of junior and mid-level analysts, providing guidance across the analytics lifecycle from conception through data mining/analysis and synthesis of results
  • Ability to travel 0-10%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.

Preferred:

  • Doctor of Philosophy (PhD) in Applied Statistics, Computer Science, Life Sciences, Industrial-Organizational Psychology, Organizational Behavior, Sociology, Economics, Anthropology, or another quantitative discipline
  • Experience in a professional services organization or large matrixed organization
  • Experience designing and building end-to-end data pipelines for reporting and analytics
  • Experience applying behavioral science frameworks to interpret workforce data and generate insight - not solely technical or statistical proficiency
  • Experience with talent systems such as OneModel or SAP

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to ski...

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