Senior Data Scientist, Vice President at STATE STREET CORPORATION — NeverHard

Who We Are Looking For We are seeking a Senior Data Scientist, Vice President to design and deliver advanced, data‑driven AI solutions supporting our Internal Audit Functions. In this hands‑on role, you will build relevant solutions leveraging statistical models, machine learning, generative AI, and agentic AI to drive measurable benefits in a regulated audit environment. This is a senior individual‑contributor role with end‑to‑end accountability for delivery. What You Will Be Responsible For Lead the end‑to‑end design of advanced analytics and AI solutions for complex audit challenges, translating ambiguous business problems into scalable, data‑driven approaches. Define solution architecture and strategic direction, evaluating multiple design patterns to ensure alignment with audit objectives, enterprise standards, and long‑term sustainability. Drive rapid prototyping and iterative delivery, incorporating stakeholder feedback while maintaining clear product vision and prioritization discipline. Optimize trade‑offs across speed, model performance, scalability, cost, and operational risk to ensure solutions are production‑ready and deliver measurable business value. Establish and own model selection frameworks, determining when to leverage existing models versus developing bespoke analytical or AI solutions. Design, develop, and refine advanced models that generate actionable, audit‑relevant insights with a strong emphasis on interpretability and decision usefulness. Set best practices for feature engineering, model architecture, and experimentation; guide the team on technical rigor and innovation. Act as primary interface with Model Risk Management and governance functions, ensuring all solutions meet enterprise standards for validation, explainability, auditability, and lifecycle management. Embed “controls by design” into all models and solutions, proactively addressing regulatory expectations and audit scrutiny. Lead governance for GenAI/LLM solutions, including prompt strategy, output reliability, grounding, traceability, and human‑in‑the‑loop controls. Anticipate emerging regulatory and risk considerations and incorporate them into solution design and documentation. Define and lead data strategy for AI use cases, including sourcing, profiling, enrichment, and representativeness, in partnership with data governance and engineering teams. Architect robust evaluation, validation, and monitoring frameworks, including metric design, benchmarking, stress testing, and drift detection. Own the end‑to‑end model lifecycle, ensuring sustained reliability and relevance through deployment and ongoing performance management. Establish scalable standards for data quality, feature reuse, and model monitoring across the portfolio of audit analytics solutions. Serve as a trusted advisor to Internal Audit, Technology, and senior leadership, shaping how AI and data science are applied within audit and risk management. Influence adoption and scaling of solutions beyond Corporate Audit, partnering with first and second lines of defense to identify enterprise‑wide use cases. Drive alignment between analytics solutions and audit methodology, ensuring outputs are actionable, defensible, and embedded into audit workflows. Partner with change management and product teams to enable adoption through training, documentation, and integration into standard operating processes. What We Value End‑to‑End Model Ownership in Regulated Environments – Proven ability to lead the full lifecycle of complex models with deep expertise in explainability, auditability, and regulatory alignment. Risk‑Focused Applied Machine Learning – Advanced capability in translating complex data patterns into prioritized, decision‑ready risk signals. Evaluation, Validation & Performance Oversight – Track record of designing fit‑for‑purpose evaluation frameworks, including metric strategy and bias detection. Strategic Data Acumen – Strong data intuition for large‑scale data sourcing, profiling, and feature engineering. Responsible GenAI / LLM Expertise – Experience developing and governing GenAI solutions with safeguards and human‑in‑the‑loop controls. Technical Leadership & Engineering Excellence – Expert‑level Python, advanced SQL, and strong software engineering discipline for scalable ML pipelines. Cloud‑Native Machine Learning (AWS) – Deep experience with SageMaker and related AWS services for scalable, automated, and cost‑optimized solutions. Executive Communication & Influence – Ability to translate complex analytical concepts into clear, concise insights for senior stakeholders. Education & Preferred Qualifications Advanced Education in a Quantitative Discipline – Bachelor’s or Master’s in Computer Science, Data Science, Statistics, Engineering, or related field. 7–10+ years of progressively senior experience in data science, machine learning, or advanced analytics within regulated environments. Expert‑Level Python & ML Ecosystem Proficiency – Advanced proficiency in pandas, scikit‑learn, TensorFlow, PyTorch, and related tools. Strong Theoretical and Practical Foundations – Deep understanding of model selection, tuning, validation, and reproducibility in production settings. Experience with Large‑Scale Data Platforms – SQL and distributed processing frameworks such as Spark, Databricks. Cloud‑Native ML Deployment Expertise – Architecture, deployment, and maintenance of ML solutions in AWS (SageMaker). Experience Operating in Controlled / Regulated Environments – Familiarity with model risk management, validation, and documentation standards. Executive‑Level Communication & Influence – Translate analytical concepts into actionable insights for senior stakeholders. Nice‑to‑Have Qualifications Application of AI in Regulated Environments – Experience designing and deploying analytics or AI solutions within Internal Audit or related regulated industries. Deep Understanding of Model Risk & Data Governance – Knowledge of model risk frameworks and data governance principles with experience embedding these in design and delivery. Advanced MLOps & Production Excellence – CI/CD for ML pipelines, automated testing, model versioning, monitoring, and incident management. Enterprise‑Grade LLM / NLP Application – Experience with prompt engineering, evaluation design, and integration into business workflows with governance controls. AI‑Driven Document & Image Intelligence – Building and scaling AI solutions for OCR, classification, and entity extraction within end‑to‑end workflows. About State Street State Street is recognized globally as a leading partner for institutional investors, providing risk management, performance, and operational efficiency solutions. Equal Opportunity Employer 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. Apply Discover more information on jobs at StateStreet.com/careers. #J-18808-Ljbffr