Senior Data Scientist, Cybersecurity Analytics & AI

STATE STREET CORPORATION; Quincy (MA); On-site; USD 90,000 - 158,000; Full time

Benefits offered by this job

401K with company match

Paid time off

Volunteer days

Employee networks

Job summary

State Street Corporation invites a Data Scientist to advance enterprise cybersecurity analytics, modeling, and risk scoring. The role blends statistical modeling, ML, graph analytics, NLP, and GenAI on large security datasets to deliver explainable insights and improve security operations.

The ideal candidate collaborates with security, engineering, governance, and risk stakeholders, translating business needs into scalable analytics and dashboards for technical and non-technical audiences.

Qualifications

• Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Cybersecurity, or equivalent practical experience.
• Strong hands-on experience with Python and SQL for analytical modeling and data manipulation.
• Experience using PySpark and Databricks to process large-scale datasets.
• Experience creating dashboards and visualizations using Power BI or similar tools.
• Familiarity with SIEM/SOAR platforms and security workflows.

Responsibilities

• Develop statistical, ML, and AI-driven models for enterprise cybersecurity datasets.
• Analyze large structured and unstructured data using Python, SQL, PySpark, and Databricks.
• Design analytics for threat detection, vulnerability prioritization, and incident enrichment.
• Apply graph analytics to uncover relationships among identities, assets, and events.
• Build reusable datasets, notebooks, models, dashboards, and monitoring outputs.

Skills

Python

SQL

Machine Learning

Graph Analytics

NLP

GenAI

Cloud

Data Visualization

Education

Bachelor's degree in CS/related field

Master's degree preferred

Tools

PySpark

Databricks

Power BI

AWS

Job description

State Street Corporation invites a Data Scientist to advance enterprise cybersecurity analytics, modeling, and risk scoring. The role blends statistical modeling, ML, graph analytics, NLP, and GenAI on large security datasets to deliver explainable insights and improve security operations.

The ideal candidate collaborates with security, engineering, governance, and risk stakeholders, translating business needs into scalable analytics and dashboards for technical and non-technical audiences.