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Nonprofit Machine Learning Jobs in Colorado (NOW HIRING)

HCVT

Senior Data & Analytics Specialist

Denver, CO · On-site

... Nonprofit Organizations, and Affordable Housing. We Live Our Core Values Our values guide us in our ... Define data models, standards, and architecture that support reporting, analytics, machine learning ...

HCVT

Senior Data & Analytics Specialist

Denver, CO · Hybrid

... Nonprofit Organizations, and Affordable Housing. We Live Our Core Values Our values guide us in our ... Define data models, standards, and architecture that support reporting, analytics, machine learning ...

HCVT

Senior Data & Analytics Specialist

Denver, CO · Hybrid

... Nonprofit Organizations, and Affordable Housing. We Live Our Core Values Our values guide us in our ... Define data models, standards, and architecture that support reporting, analytics, machine learning ...

Polycreek

Board Member - Polycreek

Denver, CO · On-site

Artificial intelligence / machine learning * Cybersecurity or trust & safety * Nonprofit governance or legal/compliance * Fundraising or philanthropy * Victim advocacy or child protection * Ability ...

Epsilon

Lead, Client Leadership

Westminster, CO

You will be accountable for elevating the quality of partnerships with nonprofit, agency, and ... A passion for using emerging technologies, including AI, machine learning, and dynamic creative ...

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Nonprofit Machine Learning information

What is a nonprofit machine learning professional?

A Nonprofit Machine Learning professional is someone who applies machine learning and data science techniques to help nonprofit organizations achieve their missions. This can include using predictive analytics to improve fundraising, optimize program delivery, or analyze the impact of initiatives. They often work with large datasets, develop algorithms, and collaborate with program staff to find data-driven solutions to social challenges. Their work helps nonprofits make more informed decisions and maximize their impact.

How does the role of a machine learning specialist in a nonprofit differ from similar roles in the private sector?

In a nonprofit setting, a Machine Learning Specialist often works with limited resources and must prioritize projects that directly support the organization's mission, such as optimizing donor outreach, improving program delivery, or analyzing social impact. Collaboration with program staff, fundraisers, and volunteers is common, requiring strong communication skills to translate technical insights into actionable strategies. Unlike the private sector, where profitability may be the primary focus, success in a nonprofit environment is measured by social outcomes and mission alignment. This role offers the opportunity to see the tangible impact of your work and can lead to leadership or strategic roles within the organization as you demonstrate value.

What are the key skills and qualifications needed to thrive as a nonprofit machine learning specialist, and why are they important?

To thrive as a Nonprofit Machine Learning Specialist, you need a strong background in data analysis, statistics, and machine learning, typically supported by a degree in computer science or a related field. Proficiency with programming languages like Python or R, experience with machine learning frameworks (such as TensorFlow or scikit-learn), and familiarity with donor management or CRM systems are highly valuable. Strong communication, problem-solving, and collaboration skills help translate technical solutions into meaningful impact for nonprofit missions. These abilities are crucial for leveraging data-driven insights to optimize resources, drive fundraising, and advance organizational goals.

What is the difference between Nonprofit Machine Learning vs Nonprofit Data Analyst?

AspectNonprofit Machine LearningNonprofit Data Analyst
Required SkillsMachine learning algorithms, programming (Python, R), statistical modelingData visualization, statistical analysis, Excel, SQL
Work EnvironmentResearch-focused, technical teams, data science projectsReporting, data interpretation, stakeholder communication
Employer & Industry UsageTech-driven nonprofits, research institutionsCharities, advocacy groups, social service agencies

Nonprofit Machine Learning roles focus on developing predictive models and advanced algorithms, requiring programming and statistical skills. Nonprofit Data Analysts primarily interpret and visualize data to inform decisions. While both roles support nonprofit missions, Machine Learning positions are more technical and research-oriented, whereas Data Analysts focus on data reporting and communication.

What are popular job titles related to Nonprofit Machine Learning jobs in Colorado?

For Nonprofit Machine Learning jobs in Colorado, the most frequently searched job titles are:

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

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

Nonprofit Machine Learning jobs near you
Infographic showing various Nonprofit Machine Learning job openings in Colorado as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, 1% Temporary, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Senior Data & Analytics Specialist

HCVT

Denver, CO • On-site

Full-time

Posted 6 days ago

Job description

Come for the Challenge. Stay for the Experience.
At HCVT, we believe every challenge presents an opportunity to positively impact our clients and people. Talented and ambitious individuals who seek limitless professional opportunities thrive at HCVT. Our team is known for its technical skill and ability to help clients address complex business issues all while investing in and supporting our people to provide a rewarding employee experience.
What We Do and Who We Serve
We offer Tax, Audit, Advisory, and Business Management services to our clients, which include private and public companies, high-net-worth individuals, and family offices. We also specialize in serving clients across the following industries: Private Equity, Real Estate & Hospitality, Media & Entertainment, High-Net-Worth Individuals, Manufacturing & Distribution, Professional Services Firms, Technology, Healthcare, Nonprofit Organizations, and Affordable Housing.
We Live Our Core Values
Our values guide us in our day-to-day interactions with our clients and each other-Integrity at our Core; Building Success Together; Passion for Excellence; and Diversity, Equity, & Inclusion. We are focused and committed to the needs of our clients and our team.
Discover How Far You Can Go.
Opportunities abound at HCVT. Our firm has experienced steady growth since its founding in 1991 and continues to expand its client service offerings, creating new opportunities for professionals to grow their careers. We make significant investments in training and provide interesting, diverse, and intellectually stimulating work for our teams-the kind of work that helps you develop and refine your skills to advance in the profession.
Hybrid Work
HCVT currently offers a hybrid work model that allows eligible employees to work both remotely and in the office, based on business needs and team coordination. When working remotely, employees are expected to meet the same performance standards, adhere to the same policies, and maintain the same level of communication, collaboration, and responsiveness as working in the office. Please note that this arrangement is not guaranteed and subject to change at any time. We will strive to provide reasonable notice of any changes to your work location or schedule whenever possible.
About the Role
The Senior Data & Analytics Specialist is responsible for designing, building, and advancing the firm's enterprise data and analytics capabilities. This role combines expertise in data engineering, business intelligence, advanced analytics, and machine learning to deliver scalable data platforms, actionable business insights, and AI-ready data assets. Working closely with business and technology leaders, the position transforms enterprise data into trusted information that improves decision-making, operational efficiency, and client outcomes.
As the Senior Data & Analytics Specialist, you will be responsible for, but not limited to, the following:
  • Enterprise Data Platform & Engineering: Design, develop, and maintain the firm's enterprise data platform, including data warehouses, data lakes, semantic models, and data pipelines. Build scalable ETL/ELT processes that integrate information across Finance, Tax, Audit, Advisory, Operations, and other business systems while ensuring data quality, reliability, governance, and performance. Define data models, standards, and architecture that support reporting, analytics, machine learning, and AI initiatives.
  • Data Analytics & Business Intelligence: Develop modern analytics solutions that provide meaningful insights into business performance and operations. Design and deliver executive dashboards, KPIs, operational reporting, and self-service analytics using Power BI and Microsoft Fabric. Partner with business stakeholders to translate analytical requirements into scalable reporting solutions while establishing best practices for data visualization, metric definitions, and analytics governance.
  • Advanced Analytics & Data Science: Apply statistical analysis, predictive modeling, forecasting, and machine learning techniques to solve complex business problems. Build analytical models that improve operational efficiency, identify trends, predict outcomes, and support strategic decision-making. Evaluate model performance, improve accuracy, and operationalize analytical solutions for enterprise use.
  • AI-Ready Data & Intelligent Solutions: Develop governed, high-quality data assets that enable AI applications, intelligent automation, and generative AI solutions. Support modern AI capabilities through semantic models, vector-ready datasets, retrieval pipelines, and data preparation processes that improve the accuracy, reliability, and scalability of AI-enabled business solutions. Partner with software engineering teams to integrate analytics and machine learning capabilities into enterprise applications and AI agents.
  • Technical Leadership & Data Strategy: Provide technical leadership in enterprise data architecture, analytics technologies, and modern data engineering practices. Evaluate emerging tools and technologies, recommend improvements to the firm's data ecosystem, and contribute to the long-term analytics and AI strategy. Promote engineering best practices, data governance standards, automation, and continuous improvement across the analytics platform.

We expect that our Staff Azure Cloud Engineer will have the following qualifications:
  • 5+ years of progressive experience in data engineering, data analytics, data science, business intelligence, or related technical disciplines.
  • Degree in Computer Science, Data Science, Analytics, Engineering, or a related technical discipline.
  • Strong experience designing relational databases, dimensional models, data warehouses, and scalable data pipelines.
  • Advanced proficiency with SQL and Python, including data transformation, automation, and analytical development.
  • Experience designing and implementing ETL/ELT processes, data integration solutions, and enterprise data models.
  • Working knowledge of statistical analysis, predictive modeling, machine learning, and model evaluation techniques.
  • Knowledge of DevOps, CI/CD, Git, and Infrastructure-as-Code practices for analytics platforms.
  • Experience with data governance, data quality, metadata management, and enterprise analytics best practices.
  • Strong analytical thinking, technical problem-solving, and the ability to translate business requirements into scalable data solutions.
  • Excellent communication skills with the ability to explain complex technical concepts to business stakeholders.

Preferred Qualifications
  • Experience within professional services, consulting, financial services, or public accounting.
  • Hands-on expertise with Microsoft Fabric, Azure Data Platform, Power BI, or comparable cloud-based analytics platforms.
  • Experience with AI-enabled data architectures, RAG pipelines, semantic search, vector databases, or LLM-powered applications.
  • Experience building production machine learning or advanced analytics solutions.
  • Master's Degree in Computer Science, Data Science, Analytics, Engineering, or a related technical discipline.

You Matter - HCVT provides a variety of benefits and perks that help sustain a healthy and thriving work environment.
  • Visit the Benefits section to learn more.

This salary range is specific to the state(s) listed and takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill set and education; experience and training; licensure and certifications; and other business and organizational needs. A reasonable estimate of the range for this position is $123,000 to $150,000.
Connect with us:
LinkedIn, Instagram, Facebook, HCVT Website
#LI-GC1
#LI-Hybrid
The ordinance requires employers to state, in all job solicitations, postings and advertisements, that the employer will consider applicants in a manner consistent with the requirements of the Fair Chance Initiative.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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About HCVT

Sourced by ZipRecruiter

Industry

Accounting services

Company size

501 - 1,000 Employees

Headquarters location

Camarillo, CA, US

Year founded

1991

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