Senior Data Science Analyst

What We'll Bring:

The senior analyst will be working with our direct and indirect products, including credit monitoring and identity protection. You would be responsible for leading monitoring of our products and their performance, analysis to determine go forward enhancements and support model development where models are a core part of our product offering or an important predictive piece of how we deliver our product.

What You'll Bring:

• Update breach risk algorithms annually and as needed when new data becomes available.
• Analyze data to support biannual updates for various TransUnion’s reports.
• Explore innovative uses of breach data by identifying correlations between breach characteristics (e.g., type, industry, etc.) and outcomes to uncover new use cases.
• Assist in evaluating methods for linking consumers to breach victimization.
• Clean, preprocess, and integrate data from multiple ‘risk feed’ sources, and present insights clearly to stakeholders.
• Apply statistical techniques to uncover trends, patterns, and actionable insights into personalized risk assessment and recommendations.
• Support user metrics analysis to inform sales, marketing, and product planning—such as identifying correlations (or causation) between viewing a risk score and user engagement, loyalty, or behavior
• Develop, implement, and maintain advanced data models to support product development and optimization. Establish and enhance ongoing monitoring programs around key performance indicators for consumer products.
• Design and execute experiments to test hypotheses and measure the impact of product changes.
• Utilize statistical methods and machine learning techniques to analyze large datasets and generate actionable insights. Present findings and recommendations to internal and external stakeholders representing a wide range of backgrounds and levels in a clear and concise manner.

Impact You'll Make:

Qualifications and Education:

• Bachelor’s or master’s degree in quantitative discipline such as Mathematics, Statistics, Engineering, or Analytics with one (1) to three (3) years of relevant professional experience.
• Proficiency with programming and data manipulation languages such as SQL, Hive, Spark; experience with statistical programs such as R or Python; high level of familiarity with Microsoft Office tools.
• Strong experience with data visualization tools (e.g., Tableau, Power BI).
• Expertise in statistical analysis and machine learning techniques.
• Proven analytical, critical thinking, and creative problem-solving skills and attention to detail.
• Strong communication skills, with the ability to convey complex data insights to non- technical stakeholders and collaborate with cross-functional teams, including product managers, engineers, and marketing, to understand business needs and deliver data-driven solutions.
• Strong project and time management skills with the ability to manage multiple assignments effectively.
• Experience working in an agile environment is a plus.

This is a hybrid position and involves regular performance of job responsibilities virtually as well as in-person at an assigned TU office location for a minimum of two days a week.