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Remote Applied Scientist Machine Learning Jobs in Washington

GRVTY

Data Scientist, Senior

Chantilly, VA · On-site +1

... in data science, machine learning, or applied analytics, with a track record of delivering ... Experience with geospatial data, imagery products, or remote sensing datasets -- familiarity with ...

GRVTY

Data Scientist, Senior

Chantilly, VA · On-site +1

... in data science, machine learning, or applied analytics, with a track record of delivering ... Experience with geospatial data, imagery products, or remote sensing datasets - familiarity with ...

10a Labs

Machine Learning Engineer

Washington, DC · On-site +1

$130K - $200K/yr

About the Role We are seeking a Machine Learning Engineer to design, build, and evaluate advanced ... Fully remote, U.S.-based * Health Benefits : Comprehensive health, dental, and vision coverage

Redhorse Corporation

Data Scientist

Arlington, VA · On-site +1

... for remote work to be determined by the program manager and customer. Essential Functions ... Bachelor's degree in a highly quantitative field (Computer Science, Machine Learning, Operational ...

Spear AI

Machine Learning Engineer

Washington, DC · On-site +1

We're seeking a skilled Machine Learning Engineer to build and deploy production ML systems for the ... Onsite / Remote / Flexible work arrangements or hybrid options (position dependent) * Relocation ...

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Remote Applied Scientist Machine Learning information

What does a remote applied scientist machine learning do?

A Remote Applied Scientist in Machine Learning develops and implements machine learning models to solve real-world problems, often from a location outside of a traditional office. Their work involves analyzing large datasets, designing algorithms, and collaborating with teams to deploy scalable solutions. They may also conduct experiments to improve model performance and stay up to date with the latest research in the field. Communication and documentation are important, as they often work with cross-functional teams remotely.

What are the key skills and qualifications needed to thrive as a remote applied scientist machine learning?

To thrive as a Remote Applied Scientist in Machine Learning, you need a strong background in mathematics, statistics, and computer science, often supported by an advanced degree and experience in ML algorithm development. Familiarity with programming languages like Python or R, machine learning frameworks such as TensorFlow or PyTorch, and tools for data processing and cloud computing is essential. Exceptional problem-solving ability, communication, and self-motivation are key soft skills for collaborating remotely and driving projects forward. These skills ensure you can independently design, implement, and communicate impactful machine learning solutions in a distributed work environment.

What can I expect in terms of collaboration and communication when working as a remote applied scientist machine learning?

As a Remote Applied Scientist in Machine Learning, you will frequently collaborate with cross-functional teams, including data engineers, product managers, and software developers. Communication typically takes place via video calls, chat platforms, and shared documentation, so strong written and verbal communication skills are essential. You may participate in regular virtual stand-ups, sprint planning, and code reviews to align on project goals and share progress. Remote work environments emphasize proactive communication and self-management to ensure seamless teamwork and project delivery.

What are the most commonly searched types of Applied Scientist Machine Learning jobs in Washington?

The most popular types of Applied Scientist Machine Learning jobs in Washington are:

What cities in Washington are hiring for Remote Applied Scientist Machine Learning jobs?

Cities in Washington with the most Remote Applied Scientist Machine Learning job openings:

Remote Applied Scientist Machine Learning jobs near you

Senior Data Scientist (Fraud Detection and Investigative Analytics)

Node.Digital

Washington, DC • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 7 days ago

Job description

Senior Data Scientist (Fraud Detection and Investigative Analytics)

Location: Herndon, VA (Remote Work)

Must have an Public Trust Clearance

KEY RESPONSIBILITIES

  • Review, maintain, and extend all existing loan fraud indicators developed by TSD, and provide authoritative expertise on analytic method selection.
  • Design, develop, test, calibrate, and implement advanced statistical and machine learning models targeting financial fraud, improper payments, and non compliance within SBA programs.
  • Build and refine both supervised and unsupervised models, including regression, Bayesian, clustering, and ensemble approaches, and tune candidate models to determine best fit.
  • Perform data quality analysis on source tables to identify abnormalities and inconsistencies, and develop repeatable processes for combining and analyzing large relational, structured, and unstructured sources.
  • Collaborate directly with criminal investigators to determine and execute analytic strategies supporting loan fraud cases, adapting analysis as case needs shift and proactively surfacing data quality issues.
  • Adhere closely to the federal rules of criminal procedure governing protected information, including Rule 6(e).
  • Develop case leads for SBA OIG investigations from model outcomes.
  • Document all methodology, test models, and production models in a form that satisfies criminal evidentiary requirements.
  • Build visualizations and dashboards that convey methodological choices, outcomes, and predictive capability, and iterate them on end user feedback.
  • Deliver findings in multiple registers: data summaries and visualizations for investigative staff, executive summaries for OIG leadership.
  • Coordinate with the data engineering seat so the architecture supports machine learning efficiently.
  • Create programming and automation techniques that improve task efficiency using SharePoint, Python, Excel, Power BI, Power Apps, and similar tools.
  • Identify new business questions that expand the scope of analysis and reporting.

Requirements

Required:

Education

Master's, Ph.D., or doctorate level equivalent degree in data science, machine learning, computer science, mathematics, or a related field. Alternatively, ten years of applied work experience in any of the same fields.

  • 5+ yearsDesigning, implementing, and maintaining advanced AI systems and predictive models, including both supervised and unsupervised models.
  • 5+ yearsDeveloping analytic rules and models using leading edge analytic tools and best practices.
  • 5+ yearsDeveloping regression, classification, and other statistical models to identify anomalies, patterns, and predictive variables.
  • 3+ yearsProviding data support for criminal investigations into financial fraud or abuse of government funds.
  • 3+ yearsManipulating data in Python. Pandas is required.
  • 3+ yearsWorking in a modern cloud environment: Azure, AWS, or GCP. Certifications preferred.
  • 2+ yearsConducting advanced data analysis in SQL, specifically SQL Server and PostgreSQL.
  • 2+ yearsDeveloping and scaling natural language processing solutions.
  • 2+ yearsPresenting methods and findings to technical and non technical stakeholders, both orally and in written products and visualizations.

PREFERRED QUALIFICATIONS

  • Cloud certification in Azure, AWS, or GCP.
  • Direct experience with SBA loan programs, including 7(a), 504, EIDL, or PPP, or with comparable federal lending or grant fraud.
  • Entity resolution, record linkage, or graph and network analysis applied to fraud.
  • Experience producing analytic products that were used in a criminal referral or prosecution.
  • Model explainability practice such as SHAP or comparable feature attribution methods.

Benefits

We are proud to offer competitive compensation and benefits packages to include

  • Medical 
  • Dental
  • Vision
  • Basic Life 
  • Health Saving Account
  • 401K matching
  • Three weeks of PTO/Sick
  • 11 Paid Holidays
  • Pre-Approved Online Training

Apply