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Remote No Experience Machine Learning Jobs in Virginia

rockITdata

Full Stack Data Scientist

Arlington, VA · On-site +1

Hands-on experience with machine learning libraries/frameworks such as TensorFlow, PyTorch, scikit ... No one is ever required to complete any monetary transactions before starting employment with ...

micro1 AI

Domain Expert - (STEM PhD)

Virginia Beach, VA · Remote

$80 - $90/hr

Remote micro1 is engaging PhD-level Engineers in Electrical, Mechanical, or Chemical disciplines to ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

Booz Allen Hamilton, Inc.

AI Engineer

Arlington, VA · On-site +1

$77K - $176K/yr

You Have: * 2+ years of experience with machine learning engineering in software engineering or ... Remote : If this position is listed as remote, there may still be occasions when you are required ...

Polar IT Services

AWS Python Developer

Reston, VA · On-site +1

$52.25 - $72/hr

AWS Python Developer with AI experience Location: Reston, VA Mode of Work: 3 Days hybrid Top Skills' Details Strong Python and AWS skills Machine Learning, LLM, GenAi experience Needs to be a hands ...

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All JobsMachine Learning JobsRemote No Experience Machine Learning JobsRemote No Experience Machine Learning Jobs in Virginia

Remote No Experience Machine Learning information

What are some typical entry-level tasks for remote machine learning roles that require no prior experience?

In remote entry-level machine learning positions that don't require experience, you'll often start with foundational tasks such as data cleaning, labeling datasets, basic exploratory data analysis, or assisting with the implementation of machine learning algorithms under supervision. You may also be responsible for maintaining project documentation and supporting more experienced team members with research or testing. Collaboration usually takes place via online platforms, so strong communication and the ability to learn new tools quickly are important. These tasks are designed to help you build foundational skills and gradually take on more complex responsibilities as you grow in the role.

What are the key skills and qualifications needed to thrive in a remote, entry-level machine learning role, and why are they important?

To thrive in a remote, entry-level machine learning role, you need a solid understanding of mathematics, programming (especially Python), and basic machine learning concepts, often gained through online courses or a relevant degree. Familiarity with technical tools such as Jupyter Notebooks, TensorFlow, or scikit-learn, and experience using version control systems like Git are commonly expected. Strong self-motivation, effective communication, and the ability to collaborate virtually make candidates stand out in remote environments. These skills and qualities are crucial for successfully contributing to projects, adapting to new technologies, and working efficiently with distributed teams.

What is the difference between Remote No Experience Machine Learning vs Remote No Experience Data Analysis?

AspectRemote No Experience Machine LearningRemote No Experience Data Analysis
Required CredentialsBasic understanding of programming, statistics, and data concepts; no formal certification neededBasic knowledge of data handling, Excel, and analytical tools; no formal certification needed
Work EnvironmentRemote, often collaborative with data science teamsRemote, often independent or team-based data review tasks
Industry UsageUsed in tech, finance, healthcare for predictive modelingUsed across industries for reporting, insights, and decision-making

While both roles are entry-level and remote, Machine Learning focuses on understanding algorithms and predictive models, whereas Data Analysis emphasizes interpreting data and generating reports. Your choice depends on whether you prefer working with algorithms and coding or analyzing data for insights.

What are the most commonly searched types of Remote Machine Learning jobs in Virginia? The most popular types of Remote Machine Learning jobs in Virginia are:
What are popular job titles related to Remote No Experience Machine Learning jobs in Virginia? For Remote No Experience Machine Learning jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Remote No Experience Machine Learning jobs in Virginia look for? The top searched job categories for Remote No Experience Machine Learning jobs in Virginia are:
What cities in Virginia are hiring for Remote No Experience Machine Learning jobs? Cities in Virginia with the most Remote No Experience Machine Learning job openings:
Remote No Experience Machine Learning jobs near you
Data Scientist - AI/ML & Advanced Analytics (Fraud Analytics & Investigative Support)

Data Scientist - AI/ML & Advanced Analytics (Fraud Analytics & Investigative Support)

Praescient Analytics

Fairfax, VA • On-site, Remote

Full-time

Retirement, PTO

Posted 20 days ago

Job description

Location: Remote (Occasional Travel May Be Required)
Clearance: Ability to obtain and maintain a Public Trust
Position Overview
Praescient Analytics is building a multidisciplinary advanced analytics team supporting federal fraud detection and investigative missions. We are seeking experienced Data Scientists with expertise in one or more advanced analytical disciplines, including artificial intelligence (AI), machine learning (ML), natural language processing (NLP), large language models (LLMs), graph analytics, and relationship discovery.
These positions will help design and implement next-generation analytical capabilities that identify hidden fraud patterns, uncover complex relationships, analyze unstructured information, and transform large, diverse datasets into actionable intelligence for investigators and oversight organizations.
The ideal candidate is a hands-on technical specialist who enjoys applying emerging analytical technologies to solve complex fraud, financial crime, and investigative challenges.
Key Responsibilities
  • Design, develop, validate, and optimize advanced analytical models supporting fraud detection and investigative missions.
  • Apply machine learning, artificial intelligence, natural language processing, graph analytics, and statistical modeling techniques to identify fraud patterns and emerging risks.
  • Analyze structured, semi-structured, and unstructured data from multiplegovernment and commercial sources.
  • Develop scalable analytical workflows using cloud-native technologies and open-source data science frameworks.
  • Collaborate with Graph Data Scientists, Data Engineers, Investigative Analysts, and Technical Analytics Managers to develop integrated analytical solutions.
  • Document analytical methodologies, model performance, validation results, and technical recommendations.
  • Support Agile software development through sprint planning, demonstrations, peer reviews, and iterative solution development.

Required Qualifications
  • Must have experience with Fraud Analysis
  • Three (3) or more years of professional experience developing advanced analytical or machine learning solutions.
  • Strong Python and SQL programming experience.
  • Experience developing, testing, validating, and improving analytical or machine learning models.
  • Experience working with cloud analytics environments.
  • Excellent analytical, written, and verbal communication skills.

Desired Experience
We are seeking candidates with demonstrated expertise in one or more of the following advanced analytics areas:
  • Artificial Intelligence & Machine Learning: Developing, validating, deploying, and optimizing machine learning and AI models using modern frameworks and best practices for predictive analytics, classification, clustering, and model evaluation.
  • Natural Language Processing (NLP) & Large Language Models (LLMs): Applying NLP, LLMs, Retrieval-Augmented Generation (RAG), semantic search, information extraction, document intelligence, and other techniques to analyze and derive insights from unstructured text.
  • Graph Analytics & Relationship Discovery: Leveraging graph databases, knowledge graphs, link analysis, network analytics, entity resolution, and relationship discovery tools (e.g., Neo4j, Cypher, i2 Analyst's Notebook) to identify hidden patterns and complex fraud networks.
  • Cloud-Native Analytics: Developing analytical solutions within modern cloud and Lakehouse environments using platforms such as Azure Databricks, Microsoft Fabric, Azure Data Lake Storage, SQL Server, Power BI, Git, or comparable technologies.
  • Fraud Analytics & Investigative Support: Applying advanced analytics to fraud detection, financial crimes, program integrity, federal benefit programs, grants, loans, emergency relief, or other government oversight and investigative missions.

What We're Looking For
We're looking for technically curious data scientists who enjoy exploring emerging technologies and applying them to real-world investigative challenges. Whether your expertise lies in machine learning, large language models, graph analytics, relationship discovery, or advanced AI techniques, you'll help build innovative analytical capabilities that strengthen government oversight, accelerate fraud detection, and support investigators in protecting the integrity of federal programs.
What you can expect from us:
  • Real opportunity for career growth in an environment where your achievements will be celebrated
  • Constant collaboration with numerous teams to ensure client success
  • A team that respects and embraces your ideas and expertise
  • Coworkers that are motivated by pursuing excellence, rather than the prospect of personal gain
  • A workplace dedicated to supporting and bettering public safety and government agencies

Benefits:
  • Competitive salary based on qualifications and experience
  • Comprehensive, Company paid healthcare for you (We pay your premiums and deductibles)
  • 401(k) with company match
  • Travel & performance incentives
  • 3 weeks paid time off (plus Federal Holidays)
  • $5K annual training allowance
  • $500 book allowance
  • Tuition reimbursement program

Praescient Analytics is an Equal Employment Opportunity employer. Employment decisions are based on merit, qualifications, experience, performance, business needs, and applicable contract requirements. Praescient does not unlawfully discriminate or provide disparate treatment based on race, ethnicity, color, religion, sex, national origin, age, disability, veteran status, genetic information, or any other status protected by applicable law.
Praescient Analytics acknowledges the applicable clause and provision updates implementing Executive Order 14398, Addressing DEI Discrimination by Federal Contractors, and the related FAR/RFO updates, including FAR 52.222-90 where applicable. Praescient does not engage in racially discriminatory DEI activities, including disparate treatment based on race or ethnicity in recruitment, hiring, promotion, contracting, program participation, training, mentoring, leadership development, or allocation of company resources. Praescient's employment and contracting decisions are made based on merit, qualifications, experience, performance, business needs, and applicable contract requirements.
Applicants selected will be subject to a government security investigation and must meet eligibility requirements for access to classified information.
US Citizenship Required
Interested Candidates: Please forward your resume to recruiting@praescientanalytics.com and please visit our website to apply online at www.praescientanalytics.applicantstack.com/x/openings.

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