We are seeking a Data Scientist to contribute to and help lead the data science efforts for a cutting-edge investigative platform used by thousands of external users. The platform serves as an essential tool for investigators and leverages machine learning, computer vision, natural language processing (NLP), embeddings, large language models (LLMs), multimodal large language models (MLLMs), and statistical analysis to process large-scale unstructured image, text, and video data.
As a Data Scientist, you will be responsible for selecting, developing, fine-tuning, evaluating, and optimizing machine learning models for scalable production environments. This includes determining when to use off-the-shelf models versus custom or fine-tuned approaches, making sound trade-offs across performance, interpretability, latency, cost, and scalability, and helping guide models from research into deployment. You will collaborate closely with a cross-functional team of DevOps engineers, software developers, data engineers, product managers, and client stakeholders to enhance the platform’s capabilities for its investigator user base.
About the role:
This role is ideal for a mission-driven individual who thrives in a dynamic and ambiguous environment, enjoys solving complex data challenges, communicates clearly with both technical and non-technical stakeholders, and is passionate about building innovative, responsible AI solutions to support investigators in sensitive, real-world contexts.
- Develop, evaluate, fine-tune, and optimize predictive models and machine learning solutions for unstructured text and image.
- Select and adapt off-the-shelf models or build custom solutions for production use, including traditional ML, deep learning, LLMs, and multimodal models.
- Make informed recommendations on model strategy and development approaches, balancing trade-offs such as accuracy, interpretability, latency, operational complexity, cost, and scalability
- Collaborate with engineering and research teams to design, build, deploy, monitor, and maintain scalable predictive systems in production
- Apply statistical methods, NLP, computer vision, embeddings, and other modern AI/ML techniques to extract insights and improve platform performance
- Research and experiment with state-of-the-art AI/ML methodologies and identify practical opportunities to apply them within the platform
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- Guide data pipeline architecture from a data science perspective, with a focus on robustness, scalability, reproducibility, and alignment with AWS and broader data engineering practices
- Help define how models should be developed, evaluated, operationalized, and monitored in production
- Ensure ML solutions are developed and applied responsibly, with careful attention to ethical and practical considerations in sensitive investigative contexts
- Identify and integrate additional data sources to enhance investigative capabilities
- Contribute directly to product development by working closely with product and client stakeholders to refine requirements, communicate findings, and deploy solutions
- Provide thought leadership on emerging data science trends and opportunities for growth
- Participate in a rotating on-call schedule to address critical emergencies and help ensure model availability
About You
You’re a great fit for this role if you have:
- 3+ years of experience in data science, machine learning, or applied AI, including selecting, building, fine-tuning, and deploying models for scalable production environments
- Bachelor’s degree in a quantitative field such as Statistics, Computer Science, Mathematics, Physical/Biological Sciences, GIS, or a related technical discipline
- Experience working with both off-the-shelf and custom or fine-tuned models across traditional ML, deep learning, and LLM-based systems
- Strong command of Python and common data science and machine learning libraries
- Hands-on experience with modern ML/AI techniques, including LLMs, MLLMs, NLP, embeddings, and related approaches
- Strong understanding of machine learning, computer vision, NLP, and statistical methodologies
- Experience working with large-scale structured and unstructured data
- Demonstrated ability to make informed trade-offs regarding model selection, implementation, evaluation, and deployment
- Ability to recommend how models should be developed and operationalized in collaboration with engineering and product teams
- Familiarity with AWS, data pipelines, and data engineering practices
- Hands-on experience with Bash, SQL, and Docker
- Strong understanding of the ethical and practical considerations involved in applying ML methods in sensitive contexts
- Ability to take ownership of technical design decisions and ensure alignment with customer and product needs
- Comfort working in an ambiguous environment with shifting priorities
- Ability to communicate clearly with both technical and non-technical stakeholders
- Strong planning, organizational, and time management skills
- Team-oriented mindset with the ability to work independently, take initiative, and collaborate cross-functionally
- Ability to obtain and maintain a U.S. national security clearance.
- U.S. citizenship is essential to comply with the government contract, agency, or federal government requirements.
LI-SW1
What’s in it For You?
- Flexibility & Work-Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset. This builds upon our flexible work arrangements, including work from anywhere for up to 8 weeks per year, empowering employees to achieve a better work-life balance.
- Career Development and Growth: By fostering a culture of continuous learning and skill development, we prepare our talent to tackle tomorrow’s challenges and deliver real-world solutions. Our Grow My Way programming and skills-first approach ensures you have the tools and knowledge to grow, lead, and thrive in an AI-enabled future.
- Industry Competitive Benefits: We offer comprehensive benefit plans to include flexible vacation, two company-wide Mental Health Days off, access to the Headspace app, retirement savings, tuition reimbursement, employee incentive programs, and resources for mental, physical, and financial wellbeing.
- Culture: Globally recognized, award-winning reputation for inclusion and belonging, flexibility, work-life balance, and more. We live by our values: Obsess over our Customers, Compete to Win, Challenge (Y)our Thinking, Act Fast / Learn Fast, and Stronger Together.
- Social Impact: Make an impact in your community with our Social Impact Institute. We offer employees two paid volunteer days off annually and opportunities to get involved with pro-bono consulting projects and Environmental, Social, and Governance (ESG) initiatives.
- Making a Real-World Impact: We are one of the few companies globally that helps its customers pursue justice, truth, and transparency. Together, with the professionals and institutions we serve, we help uphold the rule of law, turn the wheels of commerce, catch bad actors, report the facts, and provide trusted, unbiased information to people all over the world.
In the United States, Thomson Reuters offers a comprehensive benefits package to our employees. Our benefit package includes market competitive health, dental, vision, disability, and life insurance programs, as well as a competitive 401k plan with company match. In addition, Thomson Reuters offers market leading work life benefits with competitive vacation, sick and safe paid time off, paid holidays (including two company mental health days off), parental leave, sabbatical leave. These benefits meet or exceeds the requirem
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