Officer – Data Scientist
About the Role
We are seeking a highly motivated and technically skilled Data Scientist to join our AI/ML Science team as part of the Agentic AI platform initiative. The Science pillar drives advancements in LLM research, fine-tuning, evaluation frameworks, anomaly detection, and next-generation model development, partnering closely with Platform Engineering, SRE, and Pods/Business Engagement to deliver robust agentic solutions and platform features.
In this role, you will drive applied research and product-oriented data science within the Agentic AI platform initiative. Independently own domain-specific model evaluation, fine-tuning, and operationalization workstreams. This role requires deep technical skills in LLMs, graph-based reasoning, and production-scale AI deployments, as well as the ability to collaborate across engineering, product, and business teams.
Key Responsibilities
- Own BU specific AI/ML problem statements and objectives to deliver value leveraging agentic AI workflows and domain specific LLM solutions.
- Lead foundational and domain model evaluation, fine-tuning, and prompt optimization with robust data curation and governance.
- Design and implement evaluation frameworks, taxonomies, and metrics for model benchmarking and anomaly detection.
- Build and maintain knowledge graphs, embeddings, and inference engines to enable semantic search, reasoning, and scalable serving.
- Collaborate with engineering teams to deploy scalable AI solutions in production environments.
- Conduct experiments, analyze results, and communicate findings and best practices across teams.
- Stay abreast of the latest advancements in generative AI, LLMs, and agentic systems.
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or related field.
- 5+ years of overall experience in IT and 3+ years of relevant experience in applied machine learning or NLP, with hands-on work in production environments.
- Strong experience with LLMs, GenAI, or NLP, including fine-tuning and evaluation.
- Proficiency in Python and ML libraries (PyTorch, TensorFlow, Scikit-learn).
- Experience with graph databases (e.g., Neo4j, DGL), knowledge graphs, and vector stores.
- Familiarity with cloud AI/ML services (AWS, Azure, or GCP) and MLOps practices.
- Strong communication and cross-functional collaboration skills.
- Prior work on agentic AI is a big plus
Work Schedule
On-premise
Keywords
Senior Data Scientist, Generative AI, LLM, Applied Machine Learning, RAG, Agentic Applications, Python, Azure, Model Evaluation
About State Street
Across the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability. We keep our clients at the heart of everything we do, and smart, engaged employees are essential to our continued success.
We are committed to fostering an environment where every employee feels valued and empowered to reach their full potential. As an essential partner in our shared success, you’ll benefit from inclusive development opportunities, flexible work-life support, paid volunteer days, and vibrant employee networks that keep you connected to what matters most. Join us in shaping the future.
As an Equal Opportunity Employer, we consider all qualified applicants for all positions without regard to race, creed, color, religion, national origin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military and veteran status, and other characteristics protected by applicable law.
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Skills Required
- Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field
- 5+ years of overall IT experience
- 3+ years of relevant experience in applied machine learning or NLP
- Hands-on experience with production machine learning environments
- Strong experience with LLMs, generative AI, or NLP, including fine-tuning and evaluation
- Proficiency in Python and ML libraries including PyTorch, TensorFlow, and Scikit-learn
- Experience with graph databases such as Neo4j or DGL, knowledge graphs, and vector stores
- Familiarity with AWS, Azure, or GCP cloud AI/ML services
- Familiarity with MLOps practices
- Strong communication and cross-functional collaboration skills
- Prior work on agentic AI
State Street Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about State Street and has not been reviewed or approved by State Street.
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Retirement Support — Retirement support is framed as a standout component, highlighted by a 401(k) match described as 100% on the first 6% of base salary. This is positioned as a meaningful offset to less competitive cash compensation for some roles.
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Leave & Time Off Breadth — Leave and time off are portrayed as relatively robust, with references to multi-week vacation, paid holidays, sick time, and additional days tied to wellness or volunteering. This breadth is repeatedly treated as a tangible part of total rewards beyond base pay.
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Wellbeing & Lifestyle Benefits — Wellbeing and lifestyle benefits are presented as extensive, including the BeWell program, fitness discounts, onsite or supported health resources, and financial counseling. These offerings are depicted as strengthening the overall benefits proposition even when pay satisfaction is tepid.
State Street Insights
What We Do
At State Street, we partner with institutional investors all over the world to provide comprehensive financial services, including investment management, investment research and trading, and investment servicing. Whether you are an asset manager, asset owner, alternative asset manager, insurance company, pension fund or official institution, you can rely on us to be focused on your challenges. We are committed to doing what it takes to help you perform better — now and in the future
