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Union Data Science Jobs (NOW HIRING)

Data Scientist

Mclean, VA · On-site

$95 - $140/hr

Bachelor's degree in Data Science, Statistics, Mathematics, or Computer Science is required; a ... union status, gender identity, medical condition, genetic information, sexual orientation, or any ...

Position Details Position Information Recruitment/Posting Title Lecturers, Data Science Department ... union status, sex, pregnancy, gender identity or expression, disability status, liability for ...

Data Scientist

Pine Bluff, AR · On-site

$85 - $105/hr

This union gave rise to a meaningful attitude: innovability, which guides us in thinking outside ... We are searching for someone passionate about data science and advanced analytics, with aspirations ...

Data Scientist

Seattle, WA · On-site

$113K - $141K/yr

We are focused on the Credit Unions agenda, and work on high-impact projects utilizing big data ... Postgraduate school experience delivering world-class data science outcomes (2+ years preferred ...

Bachelor's degree in Data Science, Statistics, Mathematics or Computer Science is required; A ... union status, gender identity, medical condition, genetic information, sexual orientation, or any ...

Bachelor's degree in Data Science, Statistics, Mathematics or Computer Science is required; A ... union status, gender identity, medical condition, genetic information, sexual orientation, or any ...

Showing results 41-60

Union Data Science information

See salary details

$46K

$165K

$243.5K

How much do union data science jobs pay per year?

As of Aug 21, 2026, the average yearly pay for union data science in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What is a union data scientist?

A Union Data Scientist is a professional who applies data science techniques and methodologies within labor unions or organizations representing workers. Their role typically involves analyzing large datasets to support collective bargaining, improve workplace conditions, and inform union strategies. They may work with membership data, wage information, and industry trends to generate actionable insights. Union Data Scientists play a key role in helping unions make data-driven decisions to better advocate for their members.

How do union data scientists typically collaborate with union leadership and members to address workplace issues?

Union Data Scientists often work closely with union leadership, organizers, and members to analyze workplace data—such as wage trends, grievance outcomes, or safety incidents—to support collective bargaining and policy advocacy. They translate complex data findings into actionable insights that inform negotiations or campaigns, requiring strong communication and collaboration skills. Regular interactions may involve presenting data to non-technical audiences or participating in strategy sessions, making teamwork and the ability to convey technical information in accessible ways essential to the role.

What are the key skills and qualifications needed to thrive as a union data scientist, and why are they important?

To thrive as a Union Data Scientist, you need strong analytical skills, proficiency in statistics, and a background in data science or a related field, often supported by a relevant degree. Familiarity with programming languages like Python or R, data visualization tools, and database management systems is typically required. Excellent communication, problem-solving abilities, and collaboration skills help translate complex data insights to union stakeholders and support collective bargaining strategies. These skills are crucial for driving data-informed decision-making and advancing the goals of union organizations.

What is the difference between Union Data Science vs Data Analyst?

AspectUnion Data ScienceData Analyst
Required CredentialsBachelor's or higher in Data Science, Statistics, or related fields; certifications like CAP or Microsoft Certified Data AnalystBachelor's in Statistics, Mathematics, or related fields; certifications like Microsoft Certified Data Analyst or Google Data Analytics
Work EnvironmentCollaborative teams within unions or labor organizations, often project-basedOffice settings in various industries, focusing on data interpretation and reporting
Employer & Industry UsageLabor unions, advocacy groups, government agenciesCorporations, consulting firms, government agencies across multiple sectors

Union Data Scientists and Data Analysts both analyze data, but Union Data Science roles often focus on labor-related issues within union organizations, requiring similar technical skills but applied in advocacy or policy contexts. Data Analysts typically work across industries to interpret data for business decisions. The key differences lie in their work environment and primary focus areas.

More about Union Data Science jobs

What cities are hiring for Union Data Science jobs?

Cities with the most Union 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 Union Data Science jobs?

States with the most job openings for Union Data Science jobs include:

Infographic showing various Union Data Science job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Full-time

Re-posted 9 days ago


CommunityAmerica Credit Union rating

8.5

Company rating: 8.5 out of 10

Based on 5 frontline employees who took The Breakroom Quiz


Job description

TruHome Solutions is seeking a hands-on, technically strong Manager of Data Platforms to lead the foundation that powers our data and analytics capabilities. TruHome provides mortgage origination and servicing solutions to credit unions across the country, and data is central to how we serve our clients. Our platforms power outbound data feeds, operational and analytical reporting, and the insights our internal teams and credit union clients rely on every day.

This role manages a small team and is responsible for both the Data Platform (including the data warehouse, integration pipelines, and a future cloud data platform) and the BI Platform built on Power BI. The manager will run and stabilize the existing SQL Server-based environment while playing a lead role in standing up a new cloud data platform on Databricks and Azure, maturing Power BI as the enterprise BI standard, and expanding both platforms to support additional business areas.

The ideal candidate is a player-coach with depth across data engineering and BI platforms, equally effective leading a team, partnering with business stakeholders, and managing day-to-day delivery. They should be a quick business learner who can navigate the nuances of mortgage origination and servicing and communicate clearly with both technical and non-technical audiences.


  • Lead and develop a small team responsible for the Data and BI Platforms; foster a culture of technical excellence, accountability, and continuous learning.
  • Own day-to-day operations of the SQL Server data warehouse, ETL/ELT pipelines, and outbound data feeds to member credit unions; ensure reliability, accuracy, and timely delivery.
  • Own and mature the BI platform end-to-end, including Power BI environment administration, semantic model and dataset standards, workspace and capacity governance, report performance, and operational/paginated reporting. Expand its footprint and self-service adoption across TruHome business areas.
  • Help shape and execute on the data and analytics strategy for TruHome, including the design and stand-up of a new cloud data platform on Databricks and Azure.
  • Drive maturity of the enterprise data warehouse by improving data integration, modeling, quality, and documentation, so it can serve as a trusted source for outbound feeds, reporting, and future analytical use cases.
  • Embrace and apply AI capabilities, including AI-assisted development, natural-language analytics (e.g., Databricks Genie), and AI features within the BI platform, to accelerate team productivity and improve data accessibility for business users.
  • Manage the intake, prioritization, and delivery of platform work using Agile/Scrum practices.
  • Serve as a trusted partner to TruHome business leaders and credit union clients. Translate business needs into platform capabilities, communicate progress and tradeoffs clearly, and build credibility through reliable delivery.
  • Support onboarding of new credit union clients by leading the build-out of outbound data pipelines required to integrate with their core and other downstream systems.
  • Support data governance, security, privacy, and regulatory compliance requirements relevant to mortgage servicing and credit union data, partnering with risk, compliance, and information security teams.
  • Manage select vendor relationships and assist with budget planning for tools, licenses, and contractors across the data and BI platforms.

Education and Experience Requirements
  • Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, or a related quantitative or technical field required; Master’s degree preferred.
  • 8 to 12 years of progressive experience in data engineering, business intelligence, analytics, or data/BI platform roles, with meaningful exposure across both data platform and BI platform domains.
  • 3 to 5 years of experience leading or managing small technical teams, including hiring, performance management, and team development.
  • Demonstrated experience building out or standing up cloud data platforms, ideally on Azure with Databricks. Equivalent experience on other major cloud data platforms (e.g., Snowflake, AWS, GCP) will be considered if paired with strong Spark fundamentals.
  • Exposure to maturing a BI platform (establishing standards, scaling adoption, improving semantic models and report quality, and enabling self-service) is preferred.
  • Experience in mortgage origination, mortgage servicing, banking, lending, or other financial services data environments highly preferred. Candidates without direct domain experience must clearly demonstrate a track record of quickly learning new business domains.
  • Experience working in Agile/Scrum environments and managing team delivery through structured backlogs and sprints.
Required Knowledge, Skills and Abilities
  • Strong hands-on skills with SQL Server, including SSIS for ETL development and maintenance, stored procedure development, query optimization, and performance tuning.
  • Strong hands-on skills with the modern data stack: Python, PySpark, Spark SQL, and cloud data platform services (Databricks, Azure Data Lake Storage, Azure Data Factory or equivalent orchestration).
  • Solid data modeling skills across multiple paradigms (3rd Normal Form / ODS, dimensional/Kimball-style, and modern lakehouse / medallion patterns), with judgment on when each is appropriate.
  • Good working knowledge of the Power BI platform, including semantic/tabular model design, DAX, workspace and capacity management, dataset governance, and report performance tuning. Able to set technical direction and standards for the BI platform.
  • Familiarity with DevOps / DataOps practices including Git-based source control, CI/CD pipelines (Azure DevOps or GitHub Actions), code review, and environment management.
  • Awareness of data governance, security, and privacy practices relevant to regulated financial services environments.
  • Curiosity about and practical experience applying AI tools in data engineering and BI workflows (e.g., GitHub Copilot, Databricks Assistant/Genie, Power BI Copilot); willingness to experiment, evaluate, and bring forward what works.
  • Excellent written and verbal communication skills, with the ability to translate between technical and business audiences and to communicate confidently with senior leaders and external clients.
  • Effective people leader and strong stakeholder manager. Able to coach a small technical team, set expectations, push back constructively, and build long-term trust.
  • Pragmatic and outcome-oriented; able to balance maintaining a running business with iteratively introducing modern platforms and practices, and to manage competing priorities across operational support, project delivery, and platform modernization.

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