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About the Role

Drive high-impact Vulnerability remediation governance and oversight programs using AI and cloud-based solutions. This role is critical in improving operational compliance outcomes by applying advanced machine learning and optimization techniques to real-world decision-making challenges.

Responsibilities

Acquire data for vulnerability remediation and plan/develop usable datasets for modeling.
Update internal best practices for data collection and preparation.
Contribute to data integrity conversations with stakeholders, management, and threat and vulnerability management.
Evaluate team models and recommend improvements.
Drive best practices for models and develop operational models that run at scale.
Conduct thorough reviews of data analysis and modeling techniques.
Identify and invent new evaluation methods.
Research industry trends and technologies to identify strategy opportunities.
Contribute to thought leadership best practices.
Write extensible code that spans multiple features.
Develop expertise in proper debugging techniques.
Define business, customer, and solution strategy goals.
Partner with other teams to identify and explore new opportunities.
Apply a customer-oriented focus to understand needs and drive realistic customer expectations.
Act as the technical owner of one or more production-grade data science product codebases.
Lead the end-to-end delivery of decision-support software across the full product lifecycle.
Understand complex operational business problems and identify opportunities for data-driven optimization.
Drive modeling and system design decisions, balancing implementation time, system behavior, technical debt, and business value.
Prototype, build, and deliver industrial machine learning and optimization models in Python.
Design and build robust data ingestion, cleaning, and processing pipelines.
Implement orchestration pipelines and CI/CD deployment processes.
Ensure software quality through logging, error handling, and automated testing.
Harden algorithms against operational and data edge cases.
Quantify product adoption and value capture.
Engage with business stakeholders to gather requirements and feedback.
Contribute to feature prioritization and roadmap discussions.
Support integration of decision-support products into operational business processes.
Communicate modeling approaches, trade-offs, and results clearly to technical and business audiences.
Mentor and support junior team members.
Contribute to agile ways of working, including Git versioning, code reviews, and delivery predictability.
Lead design and implementation of Microsoft Copilot, AI agents, and Generative AI solutions.
Develop and deploy Copilot Agents, policy assistants, chatbot solutions, and knowledge retrieval capabilities.
Evaluate emerging AI technologies and translate business opportunities into scalable enterprise solutions.
Partner with governance, compliance, and technology teams to ensure responsible AI adoption.

Requirements

Strong experience in Data Science, Machine Learning, and Advanced Analytics to develop predictive, operational, and insight-driven solutions.
Proficiency in Python, SQL, and Data Engineering for data transformation, modeling, automation, and analytics development.
Strong proficiency in visualization tools such as Power BI and Tableau.
Strong problem definition and design thinking skills.
Comfortable working in ambiguous environments.
Experience leveraging SharePoint, Microsoft 365, and enterprise collaboration technologies.
Proven ability to design and implement API integrations and connected systems.
Experience in process mining, workflow optimization, and intelligent automation.
Strong background in solution architecture, technical design, and scalable application development.
Demonstrated success delivering analytics products and business intelligence solutions.
Excellent presentation, facilitation, and communication skills.
Knowledge of Cloud, AI, Generative AI, and Copilot technologies.
Act as a trusted technical advisor to global compliance leaders and business stakeholders.
Lead solution discussions, proof-of-concepts, demonstrations, and technology evaluations.
Translate business requirements into technical solutions and drive execution.
Mentor team members and promote adoption of modern analytics and AI practices.
Expert capability in applied machine learning, optimization, and operational research techniques.
Strong Python expertise with experience delivering production-quality data science software.
Experience working with cloud platforms and modern ML tooling.
Strong software engineering discipline including testing, CI/CD, and version control.
Ability to structure complex business and technical problems and propose pragmatic solutions.
Clear communication skills across technical and non-technical audiences.
Collaborative working style with a focus on continuous improvement.
Systems-thinking mindset with attention to detail.
Curiosity, resilience, and adaptability in fast-moving environments.
Strong commitment to delivering measurable business value.
Bachelor's OR Master's OR Doctorate Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND data-science experience.
4-6 years working on production ML or optimization software products at scale.
Demonstrated experience or a strong interest in working in customer-facing environments.
Experience in developing industrialized software, especially data science or machine learning software products.
Experience in relevant finance and banking sector is preferred.

Skills

Data Science
Machine Learning
Advanced Analytics
Python
SQL
Data Engineering
Power BI
Tableau
Design Thinking
SharePoint
Microsoft 365
API Integrations
Process Mining
Workflow Optimization
Intelligent Automation
Solution Architecture
Technical Design
Scalable Application Development
Cloud
AI
Generative AI
Copilot
Applied Machine Learning
Optimization
Operational Research
Software Engineering
Testing
CI/CD
Version Control
Communication
Complaints Investigation
Compliance Management
Corporate Governance
Critical Thinking
Data Reporting
Detail-Oriented
Governance Risk and Compliance (GRC) Platforms
Internal Auditing
Organizing
Problem Solving
Process Improvements
Vulnerability management
Cyber knowledge

Location

Remote

Work Type

Full-time

Experience Level

Senior
4-6 years

Education Level

Bachelor's Degree
Master's Degree
Doctorate Degree

Benefits

Competitive package including a wide range of benefits built around personal needs.
Inclusive development opportunities.
Flexible work-life support.
Paid volunteer days.
Vibrant employee networks.

About the Company

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.
Join us in shaping the future.

Equal Opportunity

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.