Manager II, Data Science and Analytics

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Team Overview

The Data Science and Analytics team drives advanced analytics and AI solutions to solve complex business problems and enable >Role Overview And Core Responsibilities

• Translate business strategy into a prioritized data science roadmap aligned to measurable business outcomes.

• Lead end-to-end delivery of scalable analytics and machine learning (ML) solutions, from problem definition to deployment and monitoring.
• Manage and execute multiple concurrent initiatives, ensuring alignment across cross-functional stakeholders.
• Drive measurable business impact by defining success metrics, tracking ROI, and optimizing portfolio performance.
• Establish and enforce best practices across the analytics lifecycle, including quality, reproducibility, and automation standards.
• Provide strategic guidance and analytical leadership to senior stakeholders, influencing decision-making.
• Lead, coach, and develop high-performing data science teams, fostering an inclusive and results-driven culture.
• Drive alignment across Product, Engineering, and business teams, managing dependencies and competing priorities.
• Translate complex analytical outputs into clear, executive-ready insights and actionable recommendations.
• Scale and evolve data science capabilities, including tools, frameworks, and processes across the organization.

Required Knowledge And Experiences

• Strong background in data science, analytics, or quantitative fields, supported by a Bachelor’s degree with 10+ years of experience or a Master’s/PhD with 7+ years; ensures ability to deliver complex analytics solutions at scale.

• Proven experience managing teams and delivering large-scale analytics portfolios; critical to drive measurable business impact and organizational alignment.

• Deep understanding of statistical methods, predictive analytics, and machine learning frameworks; required to design and guide robust analytical solutions.

• Experience working in cross-functional or client-facing environments; essential to build trust and influence stakeholders across technical and business teams.

• Demonstrated ability to operate in complex, matrix organizations and make high-impact decisions under ambiguity; ensures effective prioritization and execution.

Required Technical Skills

• Proficiency in Python, R, and SQL for advanced analytics and data science development.

• Experience designing and deploying ML (Machine Learning) and AI solutions in production environments.

• Knowledge of MLOps (Machine Learning Operations) principles to ensure scalability and maintainability of solutions.

• Familiarity with big data ecosystems and cloud platforms such as AWS (Amazon Web Services), GCP (Google Cloud Platform), or Azure.

• Expertise in end-to-end analytics lifecycle management, including experimentation, validation, deployment, and monitoring.

We’re also looking for the preferred skills below

• Experience in identity, fraud, security, or credit bureau data to accelerate impact in real-world use cases.

• Background in regulated industries such as financial services or insurance.

• Experience shaping global product or analytics roadmaps across multiple teams.

• Ability to influence long-term strategy across business, product, and engineering organizations.

• Exposure to large-scale, >TransUnion Job Title

  
  
  Manager II, Data Science and Analytics