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Data Science Entry Level Remote Jobs in Virginia

Anika Systems

AI Engineer

Leesburg, VA · On-site +1

This position is currently remote; however, in accordance with federal contract requirements and ... Bachelor's Degree in Computer Science, Computer Engineering, Data Science, Computational ...

Booz Allen Hamilton, Inc.

AI Developer

Arlington, VA · On-site +1

Bachelor's degree in Computer Science, Software Engineering, Data Science, or Physics Nice If You ... Remote : If this position is listed as remote, there may still be occasions when you are required ...

Pae

Entry Level Software Engineer

Dahlgren, VA · On-site +1

Engineering, Math, Computers Science, and/or Physics with entry level experience. * Must have an ... equity, market data, applicable collective bargaining agreements, and relevant laws. Benefits ...

Xenith Solutions LLC

GenAI Developer

Leesburg, VA · On-site +1

$115K - $165K/yr

Experience working in a geographically dispersed, remote team. * Understanding of Data Science principles and best practices. Xenith Solutions LLC is a Service-Disabled Veteran-Owned Small Business ...

C-MCI

Medical Billing Specialist

Fairfax, VA · On-site +1

$18.50 - $24/hr

Remote / On-site Department: Revenue Cycle Management Overview: CMCI is seeking a detail-oriented ... Collaboratewith the engineering and data science teams to train AI models forenhanced claims ...

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Data Science Entry Level Remote information

What are some typical challenges entry-level data scientists face when working remotely, and how can they overcome them?

Entry-level data scientists working remotely often encounter challenges such as limited access to mentorship, difficulty in collaborating on complex projects, and adjusting to asynchronous communication. To overcome these, it's important to proactively seek guidance from senior team members through regular check-ins, participate actively in team meetings and online forums, and document your work thoroughly for transparency. Leveraging collaborative tools like shared code repositories and communication platforms can also help maintain strong connections with your team and ensure project alignment.

What are the key skills and qualifications needed to thrive as an entry-level remote Data Scientist, and why are they important?

To thrive as an entry-level remote Data Scientist, you need a solid background in statistics, programming (often Python or R), and data analysis, typically supported by a relevant degree or certification. Familiarity with tools like Jupyter Notebook, SQL databases, and machine learning libraries such as scikit-learn or TensorFlow is commonly required. Strong problem-solving abilities, communication skills, and self-motivation are crucial soft skills for remote collaboration and project management. These competencies enable effective data-driven insights, seamless teamwork, and measurable contributions in a distributed work environment.

What is the difference between Data Science Entry Level Remote vs Data Analyst Entry Level Remote?

AspectData Science Entry Level RemoteData Analyst Entry Level Remote
Required CredentialsBachelor's in CS, Statistics, or related field; some knowledge of programming and machine learningBachelor's in Statistics, Mathematics, or related field; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentRemote, collaborative teams, often with cross-functional departmentsRemote, often working independently or with business teams
Employer & Industry UsageTech companies, finance, healthcare, e-commerceBusiness, marketing, finance, healthcare

While both roles are entry-level remote positions involving data, Data Science Entry Level Remote focuses on programming, machine learning, and predictive modeling, whereas Data Analyst Entry Level Remote emphasizes data visualization, reporting, and interpreting data for business insights. Candidates should choose based on their skills and career interests.

What are data science entry level remote jobs?

Data science entry level remote jobs are positions suitable for individuals who are just starting their careers in data science and prefer or require the flexibility to work from home or any location outside the traditional office setting. These roles typically involve tasks such as data cleaning, basic statistical analysis, creating simple data visualizations, and assisting with machine learning projects under supervision. Entry level data scientists often work closely with more experienced team members and use tools like Python, R, SQL, and Excel. Remote roles require good communication skills and self-motivation, as collaboration happens online. These positions are a great way to gain practical experience and develop technical skills in the field of data science.
What are the most commonly searched types of Data Science Remote jobs in Virginia? The most popular types of Data Science Remote jobs in Virginia are:
What are popular job titles related to Data Science Entry Level Remote jobs in Virginia? For Data Science Entry Level Remote jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Data Science Entry Level Remote jobs in Virginia look for? The top searched job categories for Data Science Entry Level Remote jobs in Virginia are:
Data Science Entry Level Remote jobs near you
Infographic showing various Data Science Entry Level Remote job openings in Virginia as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution.
AI Engineer

AI Engineer

Anika Systems

Leesburg, VA • On-site, Remote

Full-time

Posted yesterday

Job description

Anika Systems is an outcome-driven technology solutions firm that guides federal agencies in solving complex business challenges and preparing for the future. Our services span AI Strategy, Data Intelligence, AI & Machine Learning, Intelligent Automation, Enterprise Platforms and Engineering, with a specialized focus on National Security and Federal Financial programs. We are dedicated to delivering forward-thinking solutions that accelerate the critical missions of our government clients. Through our VITAL Innovation Lab, we invest heavily in research and development to anticipate mission needs and deliver cutting edge solutions.
This position is currently remote; however, in accordance with federal contract requirements and company policy, there may be future changes to work location expectations. Candidates should be prepared for the possibility of a return to the office, either partially or fully, based on client directives, contractual obligations, or company policies. Any such changes will be communicated in advance.
Must be a U.S. Citizen with the ability to obtain and maintain a government suitability clearance.
The AI Engineers will design and deliver production AI systems across our commercial platform
work and our federal modernization programs. This is a hands-on builder role on a small, senior team. Engineers
own work end-to-end including data, model integration, services, UI, infrastructure, security, and deployment. You will be expected to make sound technical calls under federal compliance, security, and procurement constraints.
Requirements:
  • Education: Bachelor's Degree in Computer Science, Computer Engineering, Data Science, Computational Linguistics, or a related field; Master's is a bonus.
  • Experience: 1-3years of professional experience building and shipping ML or NLP systems, including focus on LLM based or GenerativeAI solutions.
  • Strong production experience in Python and TypeScript, with modern web frameworks on both sides (e.g. FastAPI, React).
  • Hands-on integration of LLMs into real applications - streaming, tool / function calling, token accounting, and failure handling - across at least one of OpenAI, Anthropic, Bedrock, Vertex, or Azure OpenAI.
  • Experience designing agentic systems: multi-step workflows, retrieval-augmented generation, evaluation, and human-in-the-loop guardrails.
  • Solid relational data modeling on PostgreSQL with an async ORM and migration tooling.
  • AWS fluency (compute, storage, IAM, secrets, networking, observability) and infrastructure-as-code, ideallyTerraform.
  • Practical understanding of OAuth / OIDC, JWT, RBAC, multi-tenant isolation, and least-privilege design.
  • Disciplined testing, linting, and type-checking habits; reviewable diffs and clear written communication.

Preferred Skills
  • Federal program exposure: NIST 800-53, FedRAMP, FISMA, ATO process, or agency-specific data-handling requirements.
  • Experience with Keycloak or another OIDC provider, RLS-based multi-tenancy, or zero-trust application design.
  • Working knowledge of a data/lakehouse platform (Databricks, Snowflake) and SQL beyond CRUD.
  • Document AI / OCR pipelines and modernization of legacy enterprise workflows.
  • Production observability (CloudWatch, OpenTelemetry, Grafana) and incident-response experience.
  • Supply-chain hardening: SBOMs, dependency scanning, signed builds, threat modeling.

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