Back to jobs

Dataverse/Data Science Lead

Pay
Pay not listedSimilar roles state $118K–$193K
Work setting
Not stated
Employment
Not stated

Before you apply

Work authorization
US citizens onlyThis position requires US citizenship and the ability to obtain a CBP Background Investigation (BI) is required

What you’ll work on

Full posting
  • Lead analytical strategy and model selection for complex operational and programmatic questions

  • Design and maintain reporting-ready Dataverse data models and analytical pipelines

  • Perform hands-on analysis in Python, SQL, and Dataverse queries

  • Set analytical standards, peer review, and documentation practices

  • Coach analysts and data scientists on methods, quality assurance, and responsible AI use

From the employer’s posting
Lead the analytical strategy for complex operational, workflow, technology, and programmatic questions
Design and maintain reporting-ready Dataverse data models, tables, relationships, transformations, validation rules, business logic, and analytical pipelines.
Perform hands-on analysis using Python, SQL, Dataverse queries, and related tools
Establish analytical standards and governance practices for reproducibility, peer review, validation, documentation, version control, data-quality checks, and transparent communication of analytical assumptions and limitations.
Coach analysts, data scientists, and technical teams on data-management practices, analytical methods, quality assurance, peer review, and responsible use of data and AI-enabled capabilities.
Apply at Xenith Solutions

Posting record

Report an error

Actively hiringFirst seen by us 7 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Oct 28, 20267 days ago
Recorded sightings
8
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$118K–$193K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 3,721 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 7

Similar jobs usually come down between day 7 and day 55.

From 10,010 similar postings that came down. Coming down is not always a hire.

Xenith Solutions is hiring

7 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring is picking up
  • Its jobs tend to stay up a long time
  • 14% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • AWS
  • Azure
  • Databricks
  • Power BI
  • Snowflake
  • GCP
Where the posting names them
- Develop, review, and apply statistical models, machine-learning methods, exploratory analyses, predictive analytics, and AI/large-language-model evaluations, as appropriate. - Perform hands-on analysis using Python, SQL, Dataverse queries, and related tools; troubleshoot complex data, integration, transformation, reporting, and modeling issues. - Partner with program, operational, technical, evaluation, and data-governance stakeholders to establish appropriate baselines, denominators, comparisons, outcomes, performance measures, and evidence limitations.
- Demonstrated experience leading complex analytical efforts from problem definition through data assessment, analysis, validation, interpretation, and communication of results to technical and nontechnical stakeholders. - Strong hands-on experience using Python and SQL to develop, test, validate, and troubleshoot analytical workflows, data transformations, statistical models, and machine-learning solutions. - Experience designing and assessing data models, data pipelines, data-quality controls, validation logic, data lineage, authoritative data sources, and reporting-ready datasets.
- Establish analytical standards and governance practices for reproducibility, peer review, validation, documentation, version control, data-quality checks, and transparent communication of analytical assumptions and limitations. - Create reusable notebooks, SQL scripts, code patterns, analytical templates, Dataverse configuration standards, data dictionaries, and quality checks to improve consistency and accelerate future work. - Coach analysts, data scientists, and technical teams on data-management practices, analytical methods, quality assurance, peer review, and responsible use of data and AI-enabled capabilities.
- Experience with one or more advanced analytical methods, including predictive modeling, time-series analysis, causal inference, natural-language processing, machine learning, generative AI, or large language model evaluation. - Experience with modern data, analytics, and visualization platforms, such as Microsoft Dataverse, Databricks, Snowflake, Power BI, Azure, AWS, Google Cloud Platform, or comparable technologies. - Demonstrated ability to communicate analytical methods, results, uncertainty, assumptions, bias, data-quality concerns, and limitations clearly to leadership and other decision-makers.
- Experience working with Dataverse and the Microsoft Power Platform, including Dataverse table design, relationships, security roles, integrations, data management, reporting, and Power BI analytics. - Advanced certifications in cloud machine learning, data science, analytics, data engineering, Databricks, Azure, AWS, Google Cloud Platform, Power Platform, or comparable technologies. - Evidence of recognized technical leadership through publications, conference presentations, internal analytical standards, training development, mentoring, peer-review leadership, or leadership of enterprise-scale analytical initiatives.
- Experience designing, implementing, or evaluating NLP, generative AI, or large language model solutions, including evaluation methodologies, error analysis, bias or fairness assessment, and responsible-use considerations. - Experience working with Dataverse and the Microsoft Power Platform, including Dataverse table design, relationships, security roles, integrations, data management, reporting, and Power BI analytics. - Advanced certifications in cloud machine learning, data science, analytics, data engineering, Databricks, Azure, AWS, Google Cloud Platform, Power Platform, or comparable technologies.

Your next step

Complete your application on xenithsolutions.applytojob.com. The employer’s form will show what is required.

Applying through JazzHR

  • No account needed: one application form on the employer’s applytojob.com page.

Already applied? Track this application

About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

Xenith Solutions is a small family focused business where we focus on taking care of our employees and customers equally. We are focused on serving Federal / Civilian, Defense, and Intelligence organizations with superior service. If you want to be a part of a rapidly growing business with an exceptional culture, then you want to be a part of the Xenith Solutions family.

Xenith Solutions is seeking an inspired candidate to join our team in support of a government contract for the Department of Homeland Security (DHS).

Job Description:
Dataverse/Data Science Lead join a multidisciplinary team supporting the Department of Homeland Security (DHS) Customs and Border Protection (CBP) Program Management Office (PMO). This role is ideal for engineers who are passionate about applying technical expertise to real-world national security challenges and advancing mission-critical capabilities through research, evaluation, and informed decision-making. This position requires U.S. citizenship and the ability to obtain a CBP Background Investigation (BI) is required; active CBP BI preferred. This position requires 20% travel that may entail remote and rugged areas.
 
The Data Science Lead must be a hands-on technical leader who combines advanced statistical expertise, strong coding skills, and practical mission awareness. This individual will evaluate data quality, validate assumptions, select appropriate analytical methods, and tackle complex technical challenges while ensuring findings are accurate, defensible, and actionable.
 
The role also requires strengthening team capabilities through technical mentorship, peer review, and consistent analytical standards. The ideal candidate can communicate complex findings, uncertainty, bias, and limitations clearly to technical, operational, clinical, and executive stakeholders.


Responsibilities:
  • Lead the analytical strategy for complex operational, workflow, technology, and programmatic questions, ensuring analyses are aligned with customer priorities and decision needs.
  • Serve as the lead subject-matter expert for Microsoft Dataverse data structures, data management practices, analytical use cases, and integration with reporting, automation, and data-science solutions.
  • Assess data readiness for analytical and reporting use cases, including data quality, completeness, sensitivity, lineage, authoritative sources, access considerations, and fitness for intended measures.
  • Design and maintain reporting-ready Dataverse data models, tables, relationships, transformations, validation rules, business logic, and analytical pipelines.
  • Develop, review, and apply statistical models, machine-learning methods, exploratory analyses, predictive analytics, and AI/large-language-model evaluations, as appropriate.
  • Perform hands-on analysis using Python, SQL, Dataverse queries, and related tools; troubleshoot complex data, integration, transformation, reporting, and modeling issues.
  • Partner with program, operational, technical, evaluation, and data-governance stakeholders to establish appropriate baselines, denominators, comparisons, outcomes, performance measures, and evidence limitations.
  • Translate complex analytical findings into concise, actionable products for technical and nontechnical decision-makers, clearly communicating uncertainty, data-quality issues, assumptions, bias, and causal limitations.
  • Lead feature definition, model selection, validation strategies, error analysis, sensitivity testing, bias and fairness assessments, and interpretation for advanced analytics and machine-learning efforts.
  • Establish analytical standards and governance practices for reproducibility, peer review, validation, documentation, version control, data-quality checks, and transparent communication of analytical assumptions and limitations.
  • Create reusable notebooks, SQL scripts, code patterns, analytical templates, Dataverse configuration standards, data dictionaries, and quality checks to improve consistency and accelerate future work.
  • Coach analysts, data scientists, and technical teams on data-management practices, analytical methods, quality assurance, peer review, and responsible use of data and AI-enabled capabilities.
  • Coordinate with data engineering, platform, application-development, and Power Platform resources on data-pipeline design, integrations, model handoff, monitoring requirements, performance expectations, security considerations, and maintainability.
  • Lead technical reviews of analytical plans, data models, methods, and results to ensure the data, validation approach, assumptions, and interpretation are appropriate for the customer’s decision.
  • Partner with data owners and governance stakeholders to improve data definitions, provenance, access patterns, quality expectations, retention practices, and responsible-use controls when recurring analysis identifies systemic data issues.
  • Support development of dashboards, reports, and self-service analytical products using approved reporting and visualization tools, ensuring outputs are accurate, documented, and fit for operational use.
  • Remain current on applicable data-governance policies, privacy and security requirements, analytical methodologies, Microsoft Dataverse capabilities, and responsible AI practices.

Required Experience in years:
  • At least 9 years of progressive experience in applied data science, advanced analytics, statistical analysis, data engineering, or related analytical roles. Experience should include work in federal health, healthcare, regulated-data environments, enterprise modernization, or similarly complex mission-driven organizations.
  • Demonstrated experience leading complex analytical efforts from problem definition through data assessment, analysis, validation, interpretation, and communication of results to technical and nontechnical stakeholders.
  • Strong hands-on experience using Python and SQL to develop, test, validate, and troubleshoot analytical workflows, data transformations, statistical models, and machine-learning solutions.
  • Experience designing and assessing data models, data pipelines, data-quality controls, validation logic, data lineage, authoritative data sources, and reporting-ready datasets.
  • Experience with one or more advanced analytical methods, including predictive modeling, time-series analysis, causal inference, natural-language processing, machine learning, generative AI, or large language model evaluation.
  • Experience with modern data, analytics, and visualization platforms, such as Microsoft Dataverse, Databricks, Snowflake, Power BI, Azure, AWS, Google Cloud Platform, or comparable technologies.
  • Demonstrated ability to communicate analytical methods, results, uncertainty, assumptions, bias, data-quality concerns, and limitations clearly to leadership and other decision-makers.
  • Experience establishing or applying analytical standards for reproducibility, peer review, documentation, version control, quality assurance, validation, and responsible use of data and AI.
  • Demonstrated technical leadership experience, including mentoring analysts or data scientists, leading peer reviews, developing reusable analytical standards or assets, or managing complex analytical workstreams.

Education Requirements:
  • Master’s degree or higher in statistics, data science, operations research, public health, computer science, engineering, mathematics, or another related quantitative discipline.


Security Requirements:
  • U.S. citizenship and ability to obtain a CBP Background Investigation (BI) is required; active CBP BI preferred.

Preferred Skills:
  • Doctoral degree in statistics, data science, operations research, public health, computer science, engineering, economics, epidemiology, or a related quantitative discipline.
  • Experience supporting healthcare, federal health, clinical analytics, public health, operations research, or other domains where data context, quality, and interpretation materially affect operational or programmatic decisions.
  • Experience operationalizing analytics or machine-learning solutions through repeatable data pipelines, model monitoring, MLOps practices, model lifecycle management, or collaboration with production engineering and platform teams.
  • Experience designing, implementing, or evaluating NLP, generative AI, or large language model solutions, including evaluation methodologies, error analysis, bias or fairness assessment, and responsible-use considerations.
  • Experience working with Dataverse and the Microsoft Power Platform, including Dataverse table design, relationships, security roles, integrations, data management, reporting, and Power BI analytics.
  • Advanced certifications in cloud machine learning, data science, analytics, data engineering, Databricks, Azure, AWS, Google Cloud Platform, Power Platform, or comparable technologies.
  • Evidence of recognized technical leadership through publications, conference presentations, internal analytical standards, training development, mentoring, peer-review leadership, or leadership of enterprise-scale analytical initiatives.

Xenith Solutions LLC is a Service-Disabled Veteran-Owned Small Business founded in 2019. We provide comprehensive, timely and relevant Solutions and Business Consulting support to our customers as a key partner. Our leadership brings over a century of combined experience in Defense and Civilian markets. Our employees possess experience in all aspects of solution development from requirements creation, development, test and evaluation, fielding, and sustainment. At the core of our offerings, we provide strategy and technology solutions, giving our customers valuable insights and thought leadership on the best application of information technology to drive business objectives.

Xenith focuses on solving complex business challenges facing our customers. Our “Success Through Achievement” work ethic means our customer receive quality solutions through our commitment. We pride ourselves on tackling some of the most difficult operational requirements our customers have – ensuring an appropriate match between the mission requirements, financials, schedule, and security.

EEO

Xenith Solutions provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, marital status, amnesty, or status as a covered veteran in accordance with applicable federal, state and local laws.

EEO IS THE LAW

If you are an individual with a disability and would like to request a reasonable accommodation as part of the employment selection process, please contact Xenith Solutions.

E-Verify

As a Federal Contractor, Xenith Solutions is required to participate in the E-Verify Program to confirm eligibility to work in the United States.

Affirmative Action Plan
As a federal government contractor and based on Executive Orders and applicable laws and regulations, Xenith Solutions develops and maintains annual written Affirmative Action Plans and endeavors to hire and advance qualified minorities, females, individuals with disabilities, and protected veterans.

Source details

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay

No pay amount identified in the saved description.

Location & working pattern

Washington, DC

This passage needs a closer read in the full description.

Work authorization
Education Requirements:- Master’s degree or higher in statistics, data science, operations research, public health, computer science, engineering, mathematics, or another related quantitative discipline. Security Requirements:- U.S. citizenship and ability to obtain a CBP Background Investigation (BI) is required; active CBP BI preferred. Preferred Skills:- Doctoral degree in statistics, data science, operations research, public health, computer science, engineering, economics, epidemiology, or a related quantitative discipline.

More relevant text appears in the full description.

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.