Senior Manager, Data Science and Analytics

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Team Overview

Role Overview And Core Responsibilities

• Lead, coach, and continuously develop the Product Development Data Science team, building an inclusive culture of innovation, accountability, collaboration, and continuous learning.

• Define organizational priorities, operating models, success measures, succession plans, and leadership-development strategies that support a high-performing Data Science organization.

• Develop and execute a multi-year Data Science and AI roadmap aligned with Product Development priorities and broader business objectives.

• Identify and prioritize opportunities to apply machine learning, predictive modeling, optimization, generative artificial intelligence, and advanced analytics to high-value business challenges.

• Oversee Data Science initiatives from ideation and experimentation through production deployment, adoption, monitoring, and value realization.

• Establish best practices and governance for model development, validation, deployment, monitoring, responsible AI, and model lifecycle management.

• Partner with Product, Technology, and business leaders to translate strategic needs into scalable analytical capabilities and aligned investment decisions.

• Establish and maintain key performance indicators for organizational effectiveness, delivery predictability, solution quality, adoption, and return on analytics investments.

• Promote Agile principles and experimentation frameworks that improve organizational agility, execution predictability, and the delivery of measurable business value.

• Communicate technical findings, portfolio performance, strategic recommendations, and investment priorities clearly to executive audiences and cross-functional stakeholders.

Required Knowledge And Experiences

• Bachelor’s degree or higher in Data Science, Statistics, Computer Science, Engineering, Mathematics, Economics, or a related quantitative field, or equivalent practical experience and knowledge relevant to leading enterprise Data Science programs.

• At least 10 years of experience in Data Science, Machine Learning, Advanced Analytics, Decision Science, or a related discipline, including at least five years leading technical teams.

• Demonstrated experience building, scaling, and developing high-performing technical organizations, including organizational planning, leadership development, and talent strategy.

• Proven experience delivering large-scale machine learning and analytics solutions in production environments and translating those investments into measurable business outcomes.

• Demonstrated ability to influence senior executives, develop long-term capability roadmaps and investment plans, and align cross-functional organizations around strategic priorities.

Required Technical Skills

• Deep knowledge of ML (Machine Learning), predictive and statistical modeling, classification analytics, optimization, and advanced analytical methodologies.

• Advanced proficiency with Python, SQL, BigQuery, and modern machine learning development ecosystems.

• Experience designing and delivering scalable, production-grade analytics and artificial intelligence solutions using cloud-based AI and data platforms.

• Strong knowledge of MLOps (Machine Learning Operations), including model development, validation, deployment, monitoring, and lifecycle management.

• Strong understanding of responsible AI, model governance, risk management, experimentation, and measurement frameworks.

Desired Skills

We’re also looking for the preferred skills below. Whether you are proficient or could use some brushing up, we’re happy to support your career development and growth in:

• Master’s degree or PhD in a quantitative or technical discipline.

• Experience leading enterprise-scale machine learning, advanced analytics, or AI transformation initiatives.

• Experience supporting Fraud Prevention, Risk Management, Operational Analytics, or similarly complex decision environments.

• Experience leading globally distributed or multicultural technical teams.

• Experience presenting to executive committees or contributing to industry publications, conferences, patents, or open-source initiatives.

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TransUnion Overview:

At TransUnion, we encourage and are committed to creating a real, positive impact and shared sense of purpose within our Workforce for Good, which empowers our people to grow, innovate and contribute to a better future for our communities and customers. We strive to build an environment where our associates are in the driver’s seat of their professional development— while having access to help along the way. We recognize that success comes when our associates thrive both professionally and personally; that’s why we prioritize work/life flexibility and offer resources for our teams across the globe to collaborate and drive excellence.

Be a part of our Workforce for Good – you’ll work with great people, pioneering products and cutting-edge technology.

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