Applied Data Scientist, AI Data Platforms

Posted 4 Days Ago
Hiring Remotely in McLean, VA, USA
In-Office or Remote
103K-178K Annually
Senior level
Information Technology • Consulting
The Role
Build and operate AI-assisted data platforms using data preparation, knowledge graphs, semantic technologies, machine learning, and AI agents. Profile and reconcile enterprise data, create metadata and evaluation sets, assess language-model workflows, analyze human-review feedback, and improve platform performance. Partner with engineering teams to deploy validated solutions, maintain reproducible documentation, and communicate findings to technical and mission stakeholders. Handle sensitive data under governance and audit controls while supporting solution planning and proposals.
Summary Generated by Built In

Who Are We? 
Groundswell is a premier technology integrator and solution provider, resolutely committed to solving the most complex challenges facing federal agencies today. Our name, Groundswell, represents our commitment to be an unstoppable, seismic change in government. Ours is a small company culture with big company reach and results.  Are you ready to be audacious, be bold and drive change at a rapid pace?  Join us, where we’ll make a greater impact together.
 


What You'll do:

Groundswell is seeking a Data Scientist to help build, configure and operate an AI-assisted platform that helps organizations understand, govern and move complex enterprise data. It combines knowledge graphs, semantic search, machine learning and AI agents with human review. You will work on the ground with a small team to prepare this platform for mission use. Your work spans data preparation, knowledge management, AI evaluation and the analysis that drives platform decisions. You will make sure outputs are accurate, explainable and trusted by mission stakeholders. 

What You'll Do 

  • Translate mission and customer data questions into clear objectives, success measures and evaluation criteria. 

  • Profile, clean and characterize complex multi-source enterprise data. Identify gaps, conflicts, quality issues and relationships that affect downstream use. 

  • Build and maintain the metadata, data dictionaries and reference vocabularies that ground the data platform in each customer environment. 

  • Configure and tune AI-assisted capabilities that match, classify, rank and validate data across systems. 

  • Evaluate AI agents and language-model workflows for accuracy, grounding, consistency and failure modes. Build test sets and track quality over time. 

  • Analyze human review feedback to find systematic errors and improve platform performance. 

  • Support data validation and reconciliation so integrated or migrated data can be trusted. 

  • Partner with data, software and cloud engineers to move validated improvements into production with version control and measurable results. 

  • Create clear visualizations, narratives and briefings for technical and non-technical stakeholders, without overstating certainty. 

  • Handle sensitive data under appropriate access controls, governance and auditability. Maintain reproducible code, experiments and documentation. 

  • Contribute data science expertise to solution planning and proposal efforts as needed. 

Required Qualifications 

  • Bachelor's degree in Computer Science, Data Science, Mathematics, Statistics, Engineering or a related field; advanced degree preferred. 

  • 5+ years applying statistics, machine learning, data analysis or related quantitative methods to real-world problems. 

  • Strong Python and SQL skills with common data science libraries (pandas, NumPy, scikit-learn or comparable). 

  • Experience with knowledge graphs, graph data modeling or semantic technologies such as ontologies and taxonomies. 

  • Hands-on experience with language models or AI-assisted workflows, including evaluating output quality. 

  • Must be a U.S. Citizen per contract requirements. 

  • Must be able to obtain and maintain a Public Trust Clearance in accordance with contract requirements.

Preferred Qualifications 

  • Graph databases and query languages, such as Neo4j and Cypher. 

  • Vector search, embeddings, RAG, and AI agent frameworks such as LangGraph. 

  • Entity resolution, record linkage, and systems for matching, classifying, linking, or ranking records. 

  • Enterprise data migration, ETL, or modernization, particularly for ERP or HR systems. 

  • Time-series analysis, anomaly detection, model monitoring, and drift analysis. 

  • Cloud data and ML services on AWS or another major cloud platform. 

  • Human-in-the-loop AI workflows, experiment tracking, and model evaluation. 

  • Experience working in segmented networks, controlled-change environments, or formal authorization environments. 

  • Active Public Trust Clearance. 

  • Preference given to candidates local to the Washington, DC metro area 

Certifications 

  • A relevant certification in data science, machine learning, cloud or analytics is preferred. 


Skills:


Certification:

Why You’ll Never Want to Leave:

  • Comprehensive medical, dental, and vision plans 
  • Flexible Spending Account 
  • 4% 401K Match (immediate vesting) 
  • Paid Time Off 
  • Tuition reimbursement, certification programs, and professional development
  • Flexible work schedule
  • On-site gym and childcare option 

The salary range for this role takes into account the wide range of factors that are considered in making compensation decisions, including but not limited to skill sets, experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for any applicable geographic differential associated with the location at which the position may be filled. At Groundswell, it is not typical for an individual to be hired at or near the top of the range for their role, and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is:

$103,307.00 - $178,090.00

NOTEGroundswell does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Groundswell, and Groundswell will not be obligated to pay a placement fee.

Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, pregnancy, genetic information, disability, status as a protected veteran, or any other protected category under applicable federal, state, and local laws.

Read a copy of the Company’s Non-Discrimination Policy Statement.
Additional Resources:

  • EO 13496 Notification of Employee Rights under NLRA

  • Know your rights: Workplace Discrimination is Illegal
     

Disability Accessibility Accommodation: 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 us at [email protected] or 703-639-1777.

Skills Required

  • Bachelor's degree in Computer Science, Data Science, Mathematics, Statistics, Engineering, or a related field
  • Advanced degree
  • 5+ years applying statistics, machine learning, data analysis, or related quantitative methods to real-world problems
  • Strong Python and SQL skills with common data science libraries such as pandas, NumPy, and scikit-learn
  • Experience with knowledge graphs, graph data modeling, or semantic technologies such as ontologies and taxonomies
  • Hands-on experience with language models or AI-assisted workflows, including evaluating output quality
  • U.S. citizenship
  • Ability to obtain and maintain a Public Trust Clearance
  • Experience with graph databases and query languages such as Neo4j and Cypher
  • Experience with vector search, embeddings, RAG, and AI agent frameworks such as LangGraph
  • Experience with entity resolution, record linkage, and systems for matching, classifying, linking, or ranking records
  • Experience with enterprise data migration, ETL, or modernization, particularly for ERP or HR systems
  • Experience with time-series analysis, anomaly detection, model monitoring, and drift analysis
  • Experience with cloud data and machine learning services on AWS or another major cloud platform
  • Experience with human-in-the-loop AI workflows, experiment tracking, and model evaluation
  • Experience working in segmented networks, controlled-change environments, or formal authorization environments
  • Active Public Trust Clearance
  • Relevant certification in data science, machine learning, cloud, or analytics
  • Local to the Washington, DC metro area
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The Company
HQ: Washington, DC
360 Employees
Year Founded: 2003

What We Do

Groundswell is a highly specialized systems integrator focused on bringing modern ERP, low-code solutions, and platforms to the most complex challenges facing federal agencies. Specializing in enterprise-scale transformation, Groundswell leverages its world-class talent and SaaS intellectual property to help clients achieve their goals better, faster, and cheaper. As a premier technology integrator, we work with core partners such as Appian, SAP, Workday, and UiPath. Our expertise spans a wide range of capabilities, ensuring we can help government agencies further their objectives and redefine what citizens can expect from digital government services. Groundswell embodies our commitment to creating an unstoppable, seismic change in government. We strive to set new standards for digital government through our specialized approach, leveraging our wealth of technology and experience. Discover how Groundswell is redefining expectations for digital government at www.gswell.com

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