Cybersecurity Data Scientist , Assistant Vice President

STATE STREET CORPORATION; Kilkenny; On-site; EUR 90,000 - 120,000; Full time

Benefits offered by this job

Competitive benefits

Flexible work-life support

Volunteer days

Job summary

State Street Corporation in Kilkenny, Ireland seeks a Data Scientist specializing in cybersecurity data science and analytics. You will apply statistical modeling, ML, graph analytics, NLP, and GenAI to large-scale security datasets to generate actionable insights and improve risk prioritization.

You will collaborate with security, engineering, governance, and risk teams to translate requirements into scalable analytical solutions and deliver Power BI dashboards communicating model outputs and

Qualifications

• 5-8 years of total professional experience in data science, analytics, ML, data engineering, or related roles.
• 2-4 years applying data science techniques to cybersecurity, risk, or related enterprise data.
• Strong hands-on experience with Python and SQL for modeling and data manipulation.
• Experience using PySpark and Databricks to process and model large-scale datasets.
• Experience creating dashboards with Power BI or similar tools.
• Working knowledge of AWS data services and cloud analytics.
• Familiarity with SIEM/SOAR platforms and security workflows.
• Experience with graph analytics, NLP, GenAI, anomaly detection, and clustering.

Responsibilities

• Develop statistical, ML, and AI models across enterprise cybersecurity datasets.
• Analyze large structured and text datasets using Python, SQL, PySpark, and Databricks.
• Design analytics to support threat detection, vulnerability prioritization, and risk scoring.
• Apply graph analytics to uncover relationships among identities, assets, and threats.
• Use NLP and GenAI to summarize and enrich cybersecurity data.
• Build reusable datasets, features, notebooks, models, dashboards, and monitoring outputs.
• Collaborate with analysts, engineers, risk teams, and product owners to translate needs.
• Create Power BI reports communicating model outputs and cyber trends to diverse audiences.
• Support responsible model development with validation, privacy, and governance in regulated environments.
• Continuously evaluate emerging analytics capabilities for practical cybersecurity use.

Skills

Analytical thinking

Communication

Collaboration

Problem solving

Education

Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Cybersecurity, Information Systems, or equivalent practical experience

Master's degree or advanced coursework in Data Science, Computer Science, Statistics, Applied Mathematics, Cybersecurity, or related field

Tools

Python

SQL

PySpark

Databricks

Power BI

AWS

SIEM/SOAR

Job description

Job Title: GCS, Data Scientist

Who we are looking for We are looking for a Data Scientist to support enterprise cybersecurity data science and analytics. This role will apply statistical modeling, machine learning, graph analytics, NLP, and GenAI techniques to large-scale security datasets to generate actionable insights, improve risk prioritization, enrich security operations, and help cybersecurity teams make faster, better-informed decisions. The ideal candidate combines strong data science depth with practical cybersecurity awareness and the ability to collaborate with security, engineering, governance, and risk stakeholders.

Why This Role is important to us

Cybersecurity teams increasingly rely on high-quality data, analytical models, and AI-enabled insights to prioritize risk, detect emerging issues, and respond effectively. This Data Scientist role strengthens the organization's ability to transform cybersecurity telemetry and operational data into predictive, explainable, and actionable intelligence. The role will help improve decision-making across security operations, risk management, vulnerability prioritization, threat detection, and enterprise cybersecurity reporting.

What you will be responsible for

As a Data Scientist, you will:

• 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.

Education & Preferred Qualifications

Minimum Qualifications

• 5-8 years of total professional experience in data science, analytics, machine learning, data engineering, or related technical roles.
• 2-4 years of experience applying data science, analytics, or machine learning techniques to cybersecurity, risk, fraud, infrastructure, identity, or similarly complex enterprise datasets.
• Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Cybersecurity, Information Systems, or equivalent practical experience.
• Strong hands-on experience with Python and SQL for analytical modeling, exploratory analysis, statistical evaluation, and data manipulation.
• Experience using PySpark and Databricks to process, analyze, and model large-scale datasets.
• Experience creating clear, actionable dashboards and visualizations using Power BI or similar business intelligence tools.
• Working knowledge of AWS data and analytics services or cloud-based analytical environments.
• Familiarity with SIEM/SOAR platforms and the security workflows they support, including alert enrichment, detection analytics, triage, response, and reporting.
• Experience with one or more advanced analytical methods such as graph analytics, NLP, GenAI, anomaly detection, classification, clustering, forecasting, or recommendation techniques.
• Strong written and verbal communication skills, including the ability to document analytical assumptions, model limitations, and recommended actions.

Preferred Qualifications

• Master's degree or advanced coursework in Data Science, Computer Science, Statistics, Applied Mathematics, Cybersecurity, or a related field.
• 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.
• 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.

Technical Skills

Skill Area Expected Capabilities

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, executive-ready 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.

Additional Requirements

This is an individual contributor role with strong cross-functional collaboration expectations. The role will require sound judgment when working with sensitive cybersecurity, risk, operational, and regulated data. The candidate should be comfortable balancing exploratory data science, production-minded analytical delivery, and stakeholder communication.

What We Value

These skills will help you succeed in this role:

• 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.
• Ability to communicate complex analytical findings clearly to cybersecurity operators, engineers, risk stakeholders, and senior leaders.
• Collaborative working style with a bias for reusable solutions, documentation, operational discipline, and measurable business impact.

About State Street

State Street is one of the largest custodian banks, asset managers and asset intelligence companies in the world. From technology to product innovation we’re making our mark on the financial services industry. For more than two centuries, we’ve been helping our clients safeguard and steward the investments of millions of people. We provide investment servicing, data & analytics, investment research & trading and investment management to institutional clients. Work, Live and Grow. We make all efforts to create a great work environment. Our benefits packages are competitive and comprehensive. Details vary in locations, but you may expect generous medical care, insurance and savings plans among other perks. You’ll have access to flexible Work Program to help you match your needs. And our wealth of development programs and educational support will help you reach your full potential. Inclusion, Diversity and Social Responsibility. We truly believe our employees’ diverse backgrounds, experiences and perspective are a powerful contributor to creating an inclusive environment where everyone can thrive and reach their maximum potential while adding value to both our organization and our clients. We warmly welcome the candidates of diverse origin, background, ability, age, sexual orientation, gender identity and personality. Another fundamental value at State Street is active engagement with our communities around the world, both as a partner and a leader. You will have tools to help balance your professional and personal life, paid volunteer days, matching gift program and access to employee networks that help you stay connected to what matters to you. State Street is an equal opportunity and affirmative action employer. Discover more at StateStreet.com/careers

Information Classification: General

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. Discover more information on jobs at StateStreet.com/careers Read our CEO Statement 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…