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Executive Data Science Jobs (NOW HIRING)

You will apply deep expertise in data science, machine learning, AI techniques, large-scale data ... Create technical strategies and executive-ready materials that communicate high-impact solutions to ...

You will apply deep expertise in data science, machine learning, AI techniques, large-scale data ... Create technical strategies and executive-ready materials that communicate high-impact solutions to ...

You will apply deep expertise in data science, machine learning, AI techniques, large-scale data ... Create technical strategies and executive-ready materials that communicate high-impact solutions to ...

$175K - $200K/yr

... Science Director ... This individual will translate data into actionable strategies for the executive leadership team.

Director, Data Science

Boston, NY · On-site

$235K - $307K/yr

About the Position As the Director of Data Science at Formation Bio, you will be at the forefront ... Present complex analytical findings to senior stakeholders, including executive leadership About ...

The data science team is very much applied - their work directly makes its way into real products ... Internally, you will be expected to meet with product managers, executives and estaff, and be able ...

As Vice President of Data Science, you will lead and grow our in-house data science team. This team ... Internally, you will be expected to meet with product managers, executives and estaff, and be able ...

The data science team is very much applied - their work directly makes its way into real products ... Internally, you will be expected to meet with product managers, executives and estaff, and be able ...

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Executive Data Science information

See salary details

$26.5K

$93.6K

$184K

How much do executive data science jobs pay per year?

As of Jul 15, 2026, the average yearly pay for executive data science in the United States is $93,552.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,000.00 and $120,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Executive Data Scientist, and why are they important?

To thrive as an Executive Data Scientist, you need deep expertise in statistics, machine learning, and data analysis, typically supported by an advanced degree in a quantitative field. Proficiency with data platforms (such as SQL, Hadoop, or Spark), programming languages (like Python or R), and familiarity with data visualization tools is essential, along with certifications like Certified Analytics Professional (CAP) being advantageous. Strategic vision, leadership, and the ability to communicate complex insights to non-technical stakeholders are vital soft skills. These competencies drive effective data-driven decision-making and ensure alignment between analytics initiatives and business objectives.

What is Executive Data Science?

Executive Data Science refers to the leadership and management of data science initiatives within an organization. Professionals in this role are responsible for setting the strategic direction for data-driven projects, overseeing data teams, and ensuring that data science efforts align with business goals. They bridge the gap between technical teams and executives, translating analytical insights into actionable business strategies. Typically, Executive Data Scientists have a blend of technical expertise and strong business acumen, enabling them to make high-level decisions that impact the organization’s growth and innovation.

What is the difference between Executive Data Science vs Data Scientist?

AspectExecutive Data ScienceData Scientist
CredentialsAdvanced degrees (Master's/PhD), leadership experienceBachelor's or Master's in Data Science, Computer Science, or related fields
Work EnvironmentStrategic, leadership-focused, often in executive officesHands-on data analysis, modeling, coding in technical teams
Employer & Industry UsageSenior roles in tech, finance, consulting, and large organizationsTech companies, startups, research institutions, various industries

Executive Data Science roles focus on strategic decision-making, leadership, and overseeing data initiatives, while Data Scientists are primarily involved in technical data analysis and modeling. Both roles require strong analytical skills, but Executive Data Scientists combine technical expertise with leadership responsibilities.

How does an Executive Data Scientist typically collaborate with other departments to drive data-driven decision making?

Executive Data Scientists frequently work cross-functionally with departments such as marketing, product, finance, and operations to identify key business challenges and opportunities where data can provide strategic insights. They lead or advise interdisciplinary teams, translate complex analytics into actionable recommendations, and often present findings to senior leadership or stakeholders. Building strong relationships and understanding business objectives are crucial, as these collaborations enable the alignment of data science initiatives with organizational goals.
More about Executive Data Science jobs
What cities are hiring for Executive Data Science jobs? Cities with the most Executive Data Science job openings:
What are the most commonly searched types of Data Science jobs? The most popular types of Data Science jobs are:
What states have the most Executive Data Science jobs? States with the most job openings for Executive Data Science jobs include:
What job categories do people searching Executive Data Science jobs look for? The top searched job categories for Executive Data Science jobs are:
Infographic showing various Executive Data Science job openings in the United States as of July 2026, with employment types broken down into 50% Full Time, 25% Part Time, and 25% Contract. Highlights an 100% In-person job distribution, with an average salary of $93,552 per year, or $45 per hour.
Audit Data Science Advisor

Audit Data Science Advisor

Fannie Mae

Washington, DC

Full-time

Medical, Life

Posted 20 days ago


Job description

Playing an essential role in the U.S. economy, Fannie Mae is foundational to housing finance. Here, your expertise can help fuel purpose-driven innovation that expands access to homeownership and affordable rental housing across the country. Join Fannie Mae to grow your career and help people find a place to call home.

Job Description

As a valued contributor to our team, you will serve as a coach, mentor, and subject matter expert, driving the success of product and initiative workstreams through insights, product and change recommendations, process improvement, automation, and predictive modeling. You will apply deep expertise in data science, machine learning, AI techniques, large-scale data processing, computational programming, and practical problem solving, with the ability to clearly explain technical solutions to non-technical partners and stakeholders. As an advisor, you will partner across Audit, Technology, Enterprise AI, data science, and risk organizations to architect reusable products on a unified platform that delivers AI-enabled capabilities for stronger risk detection, continuous monitoring, evidence generation, and control-risk insights reporting. In addition, you will help shape the organization’s strategy for using and developing AI and data science to deliver data-driven insights and sound business judgment. In addition, you will provide expert guidance on well-governed models and analytical tools, partnering with senior leadership to advance business and AI transformation and innovation.

THE IMPACT YOU WILL MAKE

The Audit Data Science Advisor role will offer you the flexibility to make each day your own, while working alongside people who care so that you can deliver on the following responsibilities:

  • Partner across Audit, Technology, and platform teams to build a unified Audit platform with reusable data, analytics, automation, GenAI services, model operations, secure delivery, and enterprise controls.

  • Develop advanced analytics, AI, and data science solutions to solve complex business and technical challenges and shape technical direction.

  • Design, test, and validate audit solutions using advanced data science methods aligned with audit standards and methodology.

  • Apply data science to improve risk measurement, valuation, decision-making, and business performance.

  • Create technical strategies and executive-ready materials that communicate high-impact solutions to leaders and stakeholders.

  • Provide thought leadership on applying advanced analytics and data science to business challenges.

  • Build solutions for continuous monitoring, risk detection, automated evidence generation, and deeper insights.

  • Assess model effectiveness and fitness for use, ensure testing and monitoring, and explain key drivers and limitations.

  • Lead cross-functional teams through the model lifecycle, aligning changes with business goals.

  • Stay current on industry practices, regulations, and internal standards to ensure compliance and escalate issues as needed.

  • Advise senior leaders on priorities, balancing accuracy, speed, cost, and governance.

  • Support the Model Owner and Lead Model User in building consensus, prioritizing requirements, testing changes, resolving findings, and sharing best practices.

  • Drive continuous improvement in modeling and analytics while promoting accountability, transparency, and proactive model risk management.

  • Represent the Analytics team in internal forums, regulatory settings, and industry conferences, sharing best practices and thought leadership.

THE EXPERIENCE YOU BRING TO THE TEAM

Minimum Required Experiences

  • 6 years of related experience in data science, machine learning, and AI solution development, including GenAI workflows.

  • Master’s degree in Data Science, Economics, Mathematics, Statistics, Computer Science, or a related field.

  • Advanced proficiency in Python and core data science and machine learning techniques.

  • Experience building end-to-end data science solutions using AWS data services such as Redshift, Athena, S3, and AWS Data Wrangler.

  • Strong analytical skills to support testing, validation, model assessment, and business decision-making.

  • Strong communication skills, including the ability to explain technical concepts and solutions to non-technical partners and stakeholders.

  • Shows curiosity and adaptability in learning and responsibly applying new technologies, including artificial intelligence, to reimagine how we work.

Desired Experiences

  • PhD in Data Science, Economics, Mathematics, Statistics, Computer Science, or a related field, or equivalent additional experience.

  • Experience in Internal Audit, Risk Management, Model Risk Management, or other highly regulated environments.

  • Experience applying advanced data science methods such as regression, SVM (support vector machines), random forests, and neural networks.

  • Strong technical writing, presentation, and executive stakeholder communication skills.

  • Proven ability to influence and collaborate across cross-functional teams, including Audit, Technology, AI, and Risk partners.

  • Experience with AI engineering tools and patterns, such as Anthropic or OpenAI models and tool-calling frameworks.

Internal Audit – Data Science - Advisor

#LI-Hybrid

Qualifications

Education:

Bachelor's Level Degree

The future is what you make it to be. Discover compelling opportunities at Fanniemae.com/careers.

For most roles, employees are expected to work onsite on a regular basis at their designated office location. In-office work cadence is determined by your manager. Proximity within a reasonable commute to your designated office location is preferred unless the job is noted as open to remote.


Fannie Mae is an equal opportunity employer and considers qualified applicants for employment without regard to race, color, religion, sex, national origin, disability, age, sexual orientation, gender identity/gender expression, marital or parental status, or any other protected factor. Fannie Mae is committed to providing reasonable accommodations to qualified individuals with disabilities who are employees or applicants for employment, unless to do so would cause undue hardship to the company. If you need assistance using our online system and/or you need a reasonable accommodation related to the hiring/application process, please complete this form.

The hiring range for this role is set forth below. Final salaries will generally vary within that range based on factors that include but are not limited to, skill set, depth of experience, certifications, and other relevant qualifications. This position is eligible to participate in a Fannie Mae incentive program (subject to the terms of the program). As part of our comprehensive benefits package, Fannie Mae offers a broad range of Health, Life, Voluntary Lifestyle, and other benefits and perks that enhance an employee's physical, mental, emotional, and financial well-being. See more here.

Requisition compensation:

155000

to

209000