6+ years of US professional experience - Senior Data Scientist / AI Automation Engineer - W2 only onsite McLean, VA - local candidates only

Senior Data Scientist / AI Automation Engineer

Location: McLean, VA (Onsite) Employment Type: Full-Time contract, W2

    Must Have Qualifications: 5–7 years of relevant experience, strong Python programming skills, and an analytical mindset with a solid technical background. Must be able to proactively solve problems and able to execute. They must also have hands-on experience designing, testing, and refining prompts for large language models (LLMs). Experience building end-to-end AI solutions is a plus.

Job Description: 
We are seeking a highly analytical and execution-focused Data Scientist to support the newly formed AI Execution function. This role will focus on turning raw data and emerging AI capabilities into practical, reusable solutions that improve efficiency and decision-making across the business. 
Unlike a traditional data science role centered on modeling alone, this position emphasizes problem understanding, rapid experimentation, data operationalization, and applied AI. The ideal candidate is someone who is intellectually curious, comfortable working with imperfect data, and skilled at navigating ambiguity to deliver impact. 
Key Responsibilities 
•Partner with business teams to understand complex problem statements and translate them into AI-enabled solutions 
•Extract, clean, and structure data from raw and heterogeneous sources to enable analytics and GenAI use cases 
•Develop Python-based prototypes and tools that leverage advanced analytics and generative AI 
•Design and refine prompts to deliver reliable, explainable, and decision-ready AI outputs 
•Collaborate with data, technology, and engineering partners to align prototypes with production standards 
•Contribute reusable code, patterns, documentation, and demos to shared repositories to enable scaling and reuse 
•Support testing, validation, and iteration of AI solutions prior to broader deployment 
What Success Looks Like 
•Quickly grasps new problem domains and identifies practical paths forward 
•Produces high-quality, well-reasoned prototypes that solve real business needs 
•Elevates the quality and usability of data for multiple downstream use cases 
•Acts as a multiplier by enabling others to reuse and build on their work 
 

To apply, submit your resume through this posting.