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Vice President Machine Learning Jobs in Colorado

Vice President, Technical Operations

Denver, CO

$228K - $263K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

STACK is looking for a Vice President of Technical Operations to support all data centers across ... Partner with Learning & Development and Critical Operations SMEs to develop and deliver technical ...

New

VP of Finance

Denver, CO

$225K - $275K/yr

VP of Finance Who: A strong, stable, and rapidly growing manufacturing organization is seeking a ... If you're interested in learning more about this opportunity or would like to discuss your ...

... machine-learned bidding algorithms and demand-side platforms on a global scale. In the US ... solutions. VP Digital Sales Denver, CO Full Time COMPENSATION RANGE: 105,000.00 - 125,000.00 ...

Area VP Clinical Operations

Boulder, CO

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

As the Bristol Hospice Area VP of Clinical Operations, you will work closely with the Regional VP ... learning opportunities * Ensure locations are in continuous survey and federal audit prep mode.

Group VP of Operations (West)

Denver, CO ยท On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The Group Vice President will perform duties within the scope of their license or certification ... Execution and supervision of monthly, quarterly, and annual training programs to ensure learning ...

Area VP Clinical Operations

Boulder, CO ยท On-site

$150K - $160K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

As the Bristol Hospice Area VP of Clinical Operations, you will work closely with the Regional VP ... learning opportunities * Ensure locations are in continuous survey and federal audit prep mode.

Assistant Vice President, Events

Denver, CO ยท On-site +1

$100K - $110K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The Impact You Will Have The Assistant Vice President (AVP), reporting to the Vice President (VP), ... learning new processes. * Courtesy, respect, and thoughtfulness in teaming with colleagues and ...

Regional VP Human Resources

Denver, CO ยท On-site

$195K - $313K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Work with Group VP of HR and all HR Centers of Excellence to develop and modify strategies and programs to more effectively meet the needs of businesses and align with the corporate culture (learning ...

CO

$157K - $178K/yr

... Vice President of Instruction (VPI). As the College's Chief Academic Officer, the VPI provides ... We value diverse perspectives, foster an inclusive learning environment, and continuously work to ...

CO

$157K - $178K/yr

... Vice President of Instruction (VPI). As the College's Chief Academic Officer, the VPI provides ... We value diverse perspectives, foster an inclusive learning environment, and continuously work to ...

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Showing results 1-20

Vice President Machine Learning information

See Colorado salary details

$37.3K

$120.6K

$190.9K

How much do vice president machine learning jobs pay per year?

As of Aug 14, 2026, the average yearly pay for vice president machine learning in Colorado is $120,639.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,900.00 and $150,400.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a vice president of machine learning?

To thrive as a Vice President of Machine Learning, you need advanced expertise in machine learning, data science, and computer science, typically backed by a master's or PhD and extensive industry experience. Proficiency with platforms like TensorFlow, PyTorch, cloud computing services, and experience managing large-scale AI projects are crucial, along with a track record in leading technical teams. Exceptional leadership, strategic vision, and strong communication skills set outstanding candidates apart by enabling effective cross-functional collaboration and innovation. These skills are vital for driving organizational AI strategy, ensuring technical excellence, and delivering scalable business impact.

What does a vice president of machine learning do?

A Vice President of Machine Learning leads and oversees the strategic direction of machine learning initiatives within an organization. They manage teams of data scientists, engineers, and researchers to develop and deploy AI-driven solutions that support business goals. This role involves collaborating with other executives, setting research agendas, ensuring best practices, and staying updated with the latest advancements in the field. The VP also plays a key role in resource allocation, talent acquisition, and scaling machine learning systems across the company.

What are some common challenges faced by a vice president of machine learning when leading cross-functional teams?

A Vice President of Machine Learning often encounters challenges such as aligning diverse teams on technical priorities, managing expectations across product, engineering, and business units, and ensuring effective communication between stakeholders with varying levels of technical expertise. Balancing the need for innovation with practical business objectives and resource constraints is also a frequent challenge. Cultivating a collaborative culture and fostering ongoing professional development are key to overcoming these hurdles and driving successful outcomes.

What is the difference between Vice President Machine Learning vs Director of Machine Learning?

AspectVice President Machine LearningDirector of Machine Learning
Required CredentialsAdvanced degrees (Master's/PhD), extensive experience in MLSimilar educational background, less senior experience needed
Work EnvironmentStrategic leadership, cross-departmental collaborationProject management, team oversight
Employer & Industry UsageLarge tech firms, enterprises with AI focusTech companies, startups, research labs
Search & Comparison IntentHigh overlap in responsibilities and qualificationsRelated but more operational role

The Vice President Machine Learning typically holds a senior leadership role focused on strategic planning and cross-functional collaboration, while the Director of Machine Learning manages day-to-day projects and teams. Both roles require advanced degrees and experience in machine learning, but the VP is more involved in high-level decision-making and industry strategy.

Is vice president machine learning a high paying job?

The Vice President of Machine Learning is typically a high-level executive role with a competitive salary that reflects expertise in AI, data science, and leadership. Salaries often range from six to seven figures depending on the industry, company size, and location.

What are the most commonly searched types of Machine Learning jobs in Colorado?

The most popular types of Machine Learning jobs in Colorado are:

What job categories do people searching Vice President Machine Learning jobs in Colorado look for?

The top searched job categories for Vice President Machine Learning jobs in Colorado are:

What cities in Colorado are hiring for Vice President Machine Learning jobs?

Cities in Colorado with the most Vice President Machine Learning job openings:

VP, Advanced Analytics, Risk Adjustment

Kaiser Permanente

Denver, CO โ€ข On-site

Other

Posted 8 days ago


Job description

VP, Advanced Analytics, Risk Adjustment

Kaiser Permanente is seeking a dynamic and visionary leader to serve as VP of Advanced Analytics. This role will lead National Health Plan Risk Adjustment analytics, benchmarking, encounter submission, and strategic analytic initiatives to support risk adjustment operations across multiple lines of business. The ideal candidate will bring deep healthcare risk adjustment expertise, a strong consulting background, and an actuarial designation is preferred (ASA or FSA), with a proven track record of leveraging complex data to influence medical group partners, national and functional leaders, and drive meaningful action through data-driven insights.

This leader will also serve as an enterprise thought leader on evolving risk adjustment policy and methodology, interpreting CMS, HHS, and state regulatory developments to assess business and financial impact, guide strategic planning, inform executive decision-making, support predictive modeling and scenario analyses, and provide expertise to internal and external policy, advocacy, and stakeholder engagement efforts. This role demands strategic thinking, cross-functional collaboration, a commitment to innovation and quality, and the ability to build and inspire high-performing teams.

In this role, the VP of Advanced Analytics will build, lead, and inspire a multidisciplinary team of actuaries and advanced analytics professionals to generate actionable, decision-ready insights that directly support risk adjustment accuracy and value capture across all lines of business, including Medicare Advantage, ACA, and Medicaid. This leader will translate complex clinical, operational, financial, and regulatory information into practical strategies that improve documentation accuracy, strengthen prospective and retrospective risk adjustment programs, and enable consistent, compliant execution across regions. By partnering closely with clinical, operational, finance, care delivery, and policy stakeholders, this role will ensure analytics are embedded into workflows, support enterprise readiness for emerging risk adjustment methodologies, and drive measurable improvements in risk score integrity, quality outcomes, and financial sustainability across the organization.

This role will provide strategic analytics, benchmarking, and policy expertise to drive enterprise-wide performance, innovation, and compliance in support of Kaiser Permanentes National Health Plan Risk Adjustment organization.

Essential Responsibilities:
  • Strategic Analytics Leadership: Lead the development and execution of advanced analytics (i.e., define vision, data architecture, operating model, and success metrics) strategies that support risk adjustment operations across Medicare Advantage, ACA, and Medicaid. Utilize predictive modeling, machine learning, and statistical analyses to identify trends to drive optimal actions and outcomes, forecast risk scores, and optimize risk score accuracy capture. Ensure analytics initiatives are aligned with enterprise goals and regulatory requirements.
  • Performance Management, Reporting, and Benchmarking: Design and maintain comprehensive benchmarking frameworks to evaluate internal performance against industry and peer organizations. Develop a comprehensive and robust data analytics strategy and performance management reporting suite (e.g., KPIs and dashboards) to ensure full transparency over risk adjustment reporting for all lines of business, inclusive of benchmarking against best practices and publicly available data.
  • Encounter Submissions: This executive is accountable for accurate, timely, and compliant data submissions of the Medicare Advantage Encounter Data System (EDS) and HHS CMS EDGE server submissions. The role bridges health plan operations, data analytics, and regulatory compliance to maximize revenue accuracy and minimize financial risk by overseeing the ingestion, formatting and submissions, resolving data discrepancies, rejects, and anomalies to maximize submission acceptance rates. Partners with IT and vendors to maintain secure, scalable server infrastructure and provides executive-level dashboards tracking transfer payment estimates and data quality.
  • Risk Stratification and Prospective Algorithms to Determine Patient Risk: Evaluate and implement analytical and predictive models (e.g., risk scoring, predicting gaps in care, forecasting, margin optimization, member segmentation) that directly support business goals such as margin improvement, support quality of care delivery, pricing strategy, value-based contracting, and regulatory compliance. This role will work collaboratively across the National Health Plan, Care Delivery, and the Permanente Medical Groups to align on both strategy and execution of that data to inform clinical, quality, and operational performance levers.
  • Clinical Program Development and Quality Strategy: This role will leverage risk adjustment data and associated insights to inform clinical programs and quality strategies for use in complex care management, high-risk programs, and other 5-Star program elements. Data from this program will also inform care delivery strategies including community-based primary or supportive care, or other operating model considerations designed to improve access to care.
  • Risk Adjustment Factor Forecasting: In partnership with national finance, actuarial, and other leaders, support the accurate development of Enterprise, product level risk adjustment forecasting for financial, clinical, and other product development and actuarial modeling such as the Medicare Advantage annual bid process and the ACA rate filings, among others.
  • Thought Leadership: Collaborate with senior business stakeholders (e.g., payer/provider groups, finance, operations, strategy) to drive analytics adoption and ensure insights translate into actionable outcomes. Serve as a thought-leader within the organization: represent analytics in external forums, help set strategy for organizational data-driven transformation, mentor analytics talent.
  • Team Leadership and Development: Build and lead a high-performing analytics team (data scientists, advanced statisticians, actuaries, business intelligence engineers), establish best practices in model governance, providing business with timely, accurate and actionable insights, and moving with speed.
  • Regulatory Compliance: Establish strong data governance, ethics, model monitoring & validation processes, ensuring all analytics and benchmarking activities comply with CMS and state regulations, including HCC coding, RADV audits, and risk score submissions. Monitor regulatory changes and proactively adjust analytical methodologies to maintain compliance and optimize performance.

Basic Qualifications: Experience

  • Minimum ten (10) years of experience in healthcare risk adjustment, analytics, or actuarial leadership role, preferably within a large integrated health system, large multi-market payer, or consulting firm, with deep understanding of all actuarial aspects of commercial and government healthcare programs, including pricing, financial reporting, forecasting and risk adjustment.

Education

  • Bachelors degree in business administration, Economics, Finance, Accounting, Public Health or other quantitative discipline is required

License, Certification, Registration Additional Requirements:

  • Proven track record of translating analytics to business value: e.g., driving margin improvement, cost reduction initiatives, pricing/rate strategy, risk adjustment, regulatory analytics.
  • Strong understanding of data architecture, model deployment, cloud/enterprise analytics platforms, and ability to partner with IT/engineering.
  • Deep understanding of CMS-HCC, ACA, and CDPS, risk adjustment methodologies and Risk Adjustment Data Validation (RADV) or other coding parameters and experience managing compliance within them.
  • Experience and deep understanding in calculation and interpretation of the ACA Payment Transfer and respecting Wakely benchmarking data sets.
  • Ability to analyze risk adjustment and benchmarking data to inform business decisions (member risk score model forecasting, member turnover analyses impact on risk score)
  • Demonstrated success in managing complex organizational initiatives involving multiple functions and multiple business units/regions. Includes the identification and articulation of problems, as well as the successful buy-in, execution and benefit realization.
  • The ability to build collaborative relationships and effectively communicate with senior business leaders, including physicians.
  • Demonstrated success in building and mentoring high-performing analytics teams, fostering innovation, and scaling analytics maturity across organizations.
  • Excellent leadership, change-management, and stakeholder-management skills: able to build influence, create culture of data-driven decision-making, and scale analytics maturity.

Preferred Qualifications:

  • Masters or PhD in quantitative discipline (Statistics, Mathematics, Economics, Actuarial Science, Computer Science, Public Policy Analysis) is preferred.
  • Professional certifications such as ASA or FSA is preferred - additional credentials in data science, machine learning, or healthcare analytics are a plus.

Primary Location: California,Oakland,Ordway

Additional Locations:
  • Atlanta, GA
  • Denver, CO
  • Pasadena, CA
  • Portland, OR
  • Seattle, WA
  • Washington D.C., DC

Scheduled Weekly Hours: 40 Shift: Day Workdays: Mon-Fri Working Hours Start: 08:00 AM Working Hours End: 05:00 PM Job Schedule: Full-time Job Type: Standard Worker Location: Flexible Employee Status: Regular Employee Group/Union Affiliation: NUE Executives|NUE|Non Union Employee Job Level: Executive/VP Department: Po/Ho Corp - 3YP Core - 0308 Pay Range: $301500 - $376875 / year