Data Scientist and Analyst - Assistant Vice President
State Street · Posted Nov 6
Investment servicing, custody, asset management, and trading solutions for institutional investors
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About the role
State Street's enterprise cybersecurity data science and analytics team uses statistical modeling, machine learning, graph analytics, NLP, and GenAI on large-scale security datasets to generate actionable insights and improve risk prioritization. The role builds models, analytical datasets, dashboards, and monitoring outputs for threat detection, vulnerability prioritization, incident enrichment, cyber risk scoring, and security posture measurement. It partners with cybersecurity, engineering, governance, and risk stakeholders in a regulated financial services environment.
What you will do
- Develop statistical, machine-learning, and AI-driven models that identify patterns, anomalies, relationships, and risk signals across enterprise cybersecurity datasets.
- Analyze large structured, semi-structured, graph, time-series, and text-based security datasets using Python, SQL, PySpark, and Databricks.
- Design and deliver analytics that support threat detection, vulnerability prioritization, incident enrichment, cyber risk scoring, and security posture measurement.
- Apply graph analytics and network science techniques to uncover relationships among identities, assets, vulnerabilities, applications, alerts, events, and threat indicators.
- Use NLP and GenAI techniques to summarize, classify, enrich, and operationalize cybersecurity data such as alerts, tickets, logs, findings, playbooks, and investigation notes.
- Build reusable analytical datasets, features, notebooks, models, dashboards, and model-monitoring outputs that can scale across enterprise security use cases.
- Partner with cybersecurity analysts, data engineers, platform engineers, architects, risk teams, and product owners to translate business and security needs into analytical solutions.
- Create Power BI reports and self-service dashboards that communicate model outputs, cyber trends, operational performance, and risk insights to technical and non-technical audiences.
- Support responsible model development practices, including validation, performance monitoring, explainability, privacy, security, lineage, and documentation in a regulated environment.
- Continuously evaluate emerging analytics, ML, graph, NLP, GenAI, SIEM, SOAR, and cloud data capabilities for practical application to cybersecurity outcomes
Skills used in this role
What the employer is looking for
- Strong analytical judgment, intellectual curiosity, and the ability to frame ambiguous cybersecurity problems as measurable data science opportunities.
- Hands-on data science capability, including feature engineering, model development, statistical analysis, experimentation, and model performance evaluation.
- Practical understanding of cybersecurity concepts, including threat detection, vulnerabilities, identity and access risk, cyber incidents, SIEM/SOAR workflows, and security telemetry.
- Collaborative working style with a bias for reusable solutions, documentation, operational discipline, and measurable business impact.
- Master's degree or advanced coursework in Data Science, Computer Science, Statistics, Applied Mathematics, Cybersecurity, or a related field.
- 12 to 15 years of relevant experience in Data Analytics, Data Science and Machine Learning with statistical modelling background.
- Strong experience developing large-scale data pipelines and distributed data-processing solutions.
- Experience with Python, SQL, APIs, workflow automation, and cloud-native architectures.
- Strong communication and stakeholder collaboration skills.
- Data Science / ML : Statistical modeling, supervised and unsupervised learning, feature engineering, model evaluation, anomaly detection, experimentation, explainability.
- Programming & Data : Python, SQL, PySpark, Databricks notebooks/jobs, scalable data preparation, analytical datasets, reusable feature pipelines.
- Visualization & BI : Power BI dashboards, operational metrics, executiveready reporting, trend analysis, self-service analytical products.
- Cloud & Platforms : AWS analytical environments, cloud data services, secure data handling, scalable batch and interactive analytics.
- Cybersecurity Tools : SIEM/SOAR workflows, alert enrichment, cyber telemetry, vulnerability data, identity risk, incident and response datasets.
- Advanced Analytics : Graph analytics, NLP, GenAI, relationship analytics, entity resolution, text extraction, summarization, classification, and enrichment.
Preferred qualifications
- Experience operationalizing ML or AI solutions through feature pipelines, model monitoring, MLOps practices, reproducible notebooks, or production analytical workflows.
- Experience using graph frameworks, graph databases, knowledge graphs, entity resolution, embeddings, or relationship-based analytics for security or risk use cases.
- Experience applying NLP or GenAI to summarize, classify, extract, or enrich cybersecurity information from unstructured or semi-structured sources.
- LangGraph, Semantic Kernel, CrewAI, AutoGen, LangChain, or similar frameworks.
- Databricks, Snowflake, Spark, Kafka, Delta Lake, Iceberg, and Airflow.
- Experience with vector databases, semantic search, and enterprise RAG platforms.
- Experience implementing MLOps, LLMOps, AI observability, and evaluation frameworks.
- Knowledge of Responsible AI, data governance, and model risk management.
- Familiarity with cybersecurity data sources such as endpoint telemetry, authentication logs, cloud security events, vulnerability findings, asset inventories, application records, network events, incident tickets, or threat intelligence.
- Experience working in regulated financial services, or enterprise-scale technology environments where security, governance, privacy, and auditability are important.
- Relevant certifications or training such as Security+, CySA+, GIAC, CISSP, AWS, Databricks, or machine-learning certifications are helpful but not required.
Benefits and support
- flexible work-life support
- paid volunteer days
About State Street
State Street Corporation is a leading global financial services holding company providing institutional investors with investment servicing, investment management, and investment research and trading. Operating in more than 100 geographic markets worldwide, the company manages and administers trillions of dollars in assets through its core divisions like State Street Global Advisors and State Street Alpha. Headquartered in Boston, Massachusetts, it traces its origins back to 1792.
- Industry
- Financial Services
- Company size
- 51000+ employees
- Founded
- 1792-06-25
- Location
- Boston, Massachusetts, USA
- Funding stage
- Public Company
Leadership
Chairman and Chief Executive Officer
John Woods
Chief Financial Officer
Mostapha Tahiri
President of State Street Alpha & Chairman of Asia Pacific
Ann Fogarty
Enterprise Chief Operating Officer
President and Chief Executive Officer of State Street Investment Management
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