Who we are looking for
We are looking for a Data Scientist, Vice President with a robust background in data science, machine learning, generative AI, agentic AI applications, advanced analytics, and model lifecycle management. The ideal candidate will bring 10+ years of experience designing, developing, and operationalizing AI/ML solutions that solve complex business problems at enterprise scale. This role requires deep technical expertise, strong analytical thinking, and the ability to collaborate across business, engineering, architecture, and governance teams to deliver secure, scalable, and responsible AI solutions.
Why this role is important to us
The team you will be joining is focused on delivering secure, scalable, and responsible AI/ML solutions that help solve complex business problems and advance enterprise data science, machine learning, generative AI, agentic AI, advanced analytics, and model lifecycle management capabilities.
What you will be responsible for
As a Data Scientist, Vice President, you will:
- Design, develop, and deploy machine learning, generative AI, and agentic AI applications to address high-value business use cases.
- Perform data exploration, feature engineering, model development, evaluation, tuning, and validation using structured and unstructured data.
- Build predictive, classification, NLP, large language model-based, and agentic AI solutions for enterprise applications.
- Partner with business stakeholders, product owners, engineers, and architects to translate business problems into scalable AI/ML solutions.
- Collaborate with engineering teams to productionize models and integrate them into enterprise platforms and workflows.
- Leverage cloud platforms and modern AI/ML frameworks to build and scale solutions in secure enterprise environments.
- Ensure compliance with enterprise standards for Responsible AI, model governance, testing, monitoring, explainability, and performance validation.
- Contribute to the development of reusable AI assets, experimentation frameworks, and best practices for deployment and lifecycle management.
- Communicate findings, recommendations, and risks clearly to technical and non-technical stakeholders, including senior leadership.
- Mentor junior team members and help drive best practices in data science and applied AI delivery.
What we value
- These skills will help you succeed in this role
- Strong critical thinking, problem-solving, analytical, and decision-making skills.
- Deep technical experience in machine learning, statistical modeling, generative AI, agentic AI applications, and LLM-based solution development.
- Ability to collaborate effectively across business, engineering, architecture, and governance teams.
- Strong communication skills with the ability to present complex technical concepts in a concise and business-friendly manner.
- Commitment to Responsible AI, model governance, explainability, testing, monitoring, and performance validation.
Education & Preferred Qualifications
- BS, B-TECH, MS, or Ph.D. degree in Data Science, Computer Science, Mathematics, Statistics, or a related quantitative discipline.
- 10+ years of experience in data science, machine learning, statistical modeling, advanced analytics, generative AI, agentic AI applications, or related AI/ML solution development.
- Proficiency in Python and common AI/ML frameworks such as Scikit-learn, PyTorch, TensorFlow, Keras, or equivalent.
- Hands-on experience with NLP, LLMs, prompt engineering, embeddings, vector stores, retrieval-augmented generation (RAG), and agentic AI application patterns.
- Experience working with structured and unstructured data, feature engineering, model experimentation, and performance tuning.
- Experience with Azure and/or AWS for AI/ML development and deployment.
- Knowledge of data pipelines, APIs, and model integration patterns to operationalize AI solutions.
Additional requirements
- Experience in financial services, risk, operations, investment analytics, or other regulated enterprise environments.
- Familiarity with Responsible AI, Model Risk Management (MRM), and enterprise governance controls for AI/ML solutions.
- Experience with Databricks, Spark, SQL, LangChain, LlamaIndex, or similar AI/ML engineering tooling.
- Experience building agentic AI applications, workflow orchestration, and enterprise AI platform capabilities.
- Familiarity with MLOps / LLMOps, CI/CD, model versioning, experiment tracking, and production monitoring.
- Experience mentoring teams and influencing technical direction across multiple initiatives.
Work Requirement
- On-premise
Salary Range:
$120,000 - $202,500 AnnualThe range quoted above applies to the role in the location specified. If the candidate would ultimately work outside of the location above, the applicable range could differ.
Employees are eligible to participate in State Street’s comprehensive benefits program, which includes: our retirement savings plan (401K) with company match; insurance coverage including basic life, medical, dental, vision, long-term disability, and other optional additional coverages; paid-time off including vacation, sick leave, short term disability, and family care responsibilities; access to our Employee Assistance Program; incentive compensation including eligibility for annual performance-based awards (excluding certain sales roles subject to sales incentive plans); and, eligibility for certain tax advantaged savings plans.
For a full overview, visit https://hrportal.ehr.com/statestreet/Home.
About State StreetAcross 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.
Discover more information on jobs at StateStreet.com/careers
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Job Application Disclosure:
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
Skills Required
- 10+ years of experience in data science, machine learning, statistical modeling, advanced analytics, or AI/ML solution development.
- BS, B-TECH, MS, or PhD in Data Science, Computer Science, Mathematics, Statistics, or related quantitative discipline.
- Proficiency in Python and ML frameworks such as Scikit-learn, PyTorch, TensorFlow, or Keras.
- Hands-on experience with NLP, LLMs, prompt engineering, embeddings, vector stores, and RAG.
- Experience building agentic AI applications and LLM-based solutions.
- Experience with cloud platforms for AI/ML (Azure and/or AWS).
- Experience with Databricks, Spark, and SQL.
- Familiarity with LangChain, LlamaIndex, or similar AI engineering tooling.
- Experience with MLOps/LLMOps practices: CI/CD, model versioning, experiment tracking, and production monitoring.
- Knowledge of data pipelines, APIs, and model integration patterns to operationalize AI solutions.
- Familiarity with Responsible AI, Model Risk Management (MRM), governance controls, explainability, testing, and monitoring.
- Experience in financial services, risk, operations, investment analytics, or other regulated enterprise environments.
- Strong communication, collaboration skills, and ability to present complex technical concepts to non-technical stakeholders.
- Experience mentoring teams and influencing technical direction across initiatives.
- Work on-premise as required by the role.
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







