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Data Science Graduate Jobs in Virginia (NOW HIRING)

Senior Data Scientist

Alexandria, VA · Hybrid

$131K - $237K/yr

As a Senior Data Scientist, you will : * Lead the design, development, and deployment of advanced ... graduate degree in a quantitative or analytical field (Computer Science, Mathematics, Statistics ...

Decision Scientist II

Richmond, VA · On-site

$100K - $115K/yr

... Data Science, Analytics, Computer Science, Applied Mathematics or Engineering 3. Must be able to ... graduate degree The annual base salary for this position is $100,000 - $115,000. General ...

Showing results 21-40

Data Science Graduate information

See Virginia salary details

$37.2K

$121.7K

$194.8K

How much do data science graduate jobs pay per year?

As of Sep 9, 2026, the average yearly pay for data science graduate in Virginia is $121,686.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,700.00 and $134,800.00 per year, depending on experience, location, and employer.

What is a data science graduate?

Data Science Graduates are individuals who have recently completed a degree or certification program in data science or a related field. They possess foundational knowledge in statistics, programming, and data analysis, and are equipped to apply these skills in real-world scenarios. These graduates are typically proficient in tools such as Python, R, SQL, and data visualization platforms, and are prepared for entry-level roles in data analytics, machine learning, or business intelligence. Their education often includes hands-on projects and internships to build practical experience. Data Science Graduates are in high demand across industries that rely on data-driven decision making.

What does a data science graduate do?

As a Data Science Graduate, you can expect to work on a variety of projects such as data cleaning, exploratory data analysis, and building predictive models under the guidance of senior team members. Typical responsibilities include preparing datasets, validating model outputs, and presenting findings to both technical and non-technical stakeholders. You’ll often collaborate with data engineers, software developers, and business analysts to ensure your solutions align with organizational goals. This early-career role is a great opportunity to learn industry-standard tools, gain mentorship, and build a portfolio of impactful projects.

What are the key skills and qualifications needed to thrive as a data science graduate?

To thrive as a Data Science Graduate, you need strong analytical skills, a solid understanding of statistics, and proficiency in programming languages like Python or R, typically backed by a relevant degree. Familiarity with data visualization tools (e.g., Tableau), machine learning frameworks (e.g., scikit-learn, TensorFlow), and database management systems (e.g., SQL) is highly valuable. Strong communication, problem-solving, and adaptability help you convey insights and collaborate effectively with diverse stakeholders. These skills enable you to extract meaningful information from data, drive informed decisions, and add value to organizations in a data-driven world.

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

AspectData Science GraduateData Analyst
Required CredentialsDegree in Data Science, Computer Science, or related fieldDegree in Statistics, Mathematics, or related field
Work EnvironmentInternships, entry-level roles in tech or finance companiesBusiness, marketing, or finance departments across industries
Employer & Industry UsageTech firms, startups, research institutionsCorporations, consulting firms, government agencies
Common Search & ComparisonYesYes

Data Science Graduates typically focus on building models, machine learning, and advanced analytics, often requiring programming skills and a strong foundation in data science concepts. Data Analysts primarily interpret data, generate reports, and support decision-making with statistical tools. While both roles analyze data, Data Science Graduates usually work on more complex modeling tasks, whereas Data Analysts focus on data interpretation and visualization.

Infographic showing various Data Science Graduate job openings in Virginia as of September 2026, with employment types broken down into 89% Full Time, and 11% Part Time. Highlights an 100% In-person job distribution, with an average salary of $121,686 per year, or $58.5 per hour.

Data Scientist - NLP / Generative AI

Arlington, VA • On-site

$150 - $200/hr

Other

Medical, Dental, Vision, Retirement

Re-posted 4 days ago


Job description

Jobs / Data Scientist - NLP / Generative AI

Data Scientist - NLP / Generative AI

Full-time

About the Role

Data Scientist – NLP / Generative AILocation: Hybrid – Arlington, VirginiaEmployment Type: Full-timeBizFirst is assisting our client with the hiring of a Data Scientist specializing in natural language processing and generative AI to help the organization move from early experimentation into production-ready AI capabilities. This is a hands-on research and engineering role where you will own the design and delivery of NLP and GenAI solutions applied directly to the client’s most complex internal workflows.Our client is a mid-market professional services organization that is actively rethinking how it designs and executes its core business operations through artificial intelligence and automation. The company is building a dedicated AI capability to embed machine learning and generative AI into its most critical internal workflows – from decision support and process automation to real-time analytics and intelligent document processing.What will you doThe ideal candidate brings 5–8 years of applied data science experience with a deep specialization in NLP and a working command of modern generative AI techniques. You have built production NLP systems, worked with transformer-based architectures, and have direct experience with large language models – including fine-tuning, prompt engineering, and retrieval-augmented generation (RAG). You are comfortable moving between research and engineering as the work demands.

Responsibilities
  • Design and build NLP and generative AI solutions applied to internal business processes, including document understanding, classification, summarization, and conversational AI.
  • Develop, fine-tune, and evaluate large language models and transformer-based architectures for domain-specific applications.
  • Build and iterate on retrieval-augmented generation (RAG) systems, embedding pipelines, and vector search infrastructure.
  • Work closely with business and operations stakeholders to scope problems, define evaluation criteria, and validate model outputs against real-world requirements.
  • Analyze and interpret model behavior, identify failure modes, and develop mitigation strategies to ensure reliable, responsible outputs.
  • Collaborate with ML engineers and platform teams to move experiments into production pipelines.
  • Document experimental methodology, data lineage, and model evaluations to support reproducibility and knowledge sharing.
  • Stay current on developments in NLP research and GenAI tooling, bringing relevant advances into the team’s work quickly.
Requirements
  • US Citizen or Permanent Resident authorized to work in the United States.
  • Experience: 5–8 years of applied data science experience with a strong focus on natural language processing and text-based systems.
  • NLP & GenAI: Hands-on experience with transformer architectures (BERT, GPT, T5, or similar), fine-tuning workflows, and production deployment of language models.
  • RAG & Embeddings: Direct experience building retrieval-augmented generation pipelines, vector databases (Pinecone, Weaviate, FAISS, or equivalent), and semantic search systems.
  • Programming: Strong Python skills; proficiency with HuggingFace Transformers, LangChain, or similar GenAI tooling.
  • Evaluation: Experience designing rigorous evaluation frameworks for generative models, including human evaluation, LLM-as-judge approaches, and automated benchmarking.
  • Preferred: Experience applying NLP in a professional services, legal, finance, or consulting domain.
  • Familiarity with responsible AI practices, including bias assessment, output auditing, and hallucination mitigation.
  • Background in information extraction, named entity recognition (NER), or document intelligence.
  • Experience with cloud-based GenAI services (OpenAI API, Anthropic API, AWS Bedrock, Azure OpenAI, or GCP Vertex AI).
  • Graduate degree (MS or PhD) in Computer Science, Computational Linguistics, Statistics, or a related field.
Benefits
  • Family Health Care (54% cost covered for the entire family)
  • Family Dental (54% cost covered for the entire family)
  • Family Vision (54% cost covered for the entire family)
  • Flexible Spending Account
  • Performance bonuses tied to project and delivery milestones
  • Lifetime Event Bonuses (e.g., new child, marriage)
  • Profit-sharing arrangement for any work brought into the company
  • Unlimited Leave with Approval
  • 401k – 100% employer match on first 4% invested
  • $1,500 annual training and conference budget

Job Type: Full-time, Permanent Position

Work Authorization:US Citizen or Permanent Resident; no active security clearance required.

Schedule:Monday to Friday

Work Location:Hybrid – Arlington, Virginia

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