AI/ML Hybrid Data Scientist
Tysons, Virginia
Contract
$43/hr - $63/hr
*Must be a US citizen eligible to obtain a public clearance to apply.
A cybersecurity solutions company that leverages data and AI to protect enterprises from evolving threats is hiring a Data Scientist with 2+ years of experience to build predictive models, automate pipelines, and deliver analytics that strengthen enterprise security operations. You will also apply machine learning techniques such as regression, classification, NLP, and neural networks. This is a hands-on opportunity to collaborate across cybersecurity, data, and engineering teams to create AI-powered solutions that drive both efficiency and security at scale.
In this role you will build/maintain data pipelines, develop/deploy ML models, use APIs to automate security workflows, and create dashboards using visualization tools.
The team is based in Washington, DC and this would be a hybrid role (4 days onsite). In this position, you will use Python, SQL, APIs, visualization tools, and modern ML tools.
You will receive the following benefits:
- Medical Insurance - Four medical plans to choose from for you and your family
- Dental & Orthodontia Benefits
- Vision Benefits
- Health Savings Account (HSA)
- Health and Dependent Care Flexible Spending Accounts
- Voluntary Life Insurance, Long-Term & Short-Term Disability Insurance
- Hospital Indemnity Insurance
- 401(k) including match with pre and post-tax options
- Paid Sick Time Leave
- Legal and Identity Protection Plans
- Pre-tax Commuter Benefit
- 529 College Saver Plan
Motion Recruitment Partners (MRP) is an Equal Opportunity Employer. All applicants must be currently authorized to work on a full-time basis in the country for which they are applying, and no sponsorship is currently available. Employment is subject to the successful completion of a pre-employment screening. Accommodation will be provided in all parts of the hiring process as required under MRP’s Employment Accommodation policy. Applicants need to make their needs known in advance.