Sr Consultant- Data Analysis

TransUnion is seeking a Senior Consultant in Data Analysis to lead advanced analytics initiatives that support identity graph enablement, impact analysis, cloud cost optimization, AI innovation, and the globalization of identity solutions. This hybrid role requires a minimum of two days per week in-office presence, with the remainder performed virtually. The successful candidate will drive data quality improvements, regionalization efforts, and serve as a mentor for junior analysts while effectively communicating insights to business stakeholders.

Key Responsibilities

- Lead root cause analysis and resolve complex business challenges using advanced analytical techniques, including statistical modeling, machine learning, and AI methodologies to generate actionable insights.
- Develop data-driven recommendations that accelerate decision-making and identify opportunities to automate processes for enhanced operational efficiency.
- Drive initiatives to improve the quality, coverage, accuracy, and precision of the identity graph by analyzing identity resolution performance and recommending enhancements to matching and linking methods.
- Evaluate new data sources to strengthen identity graph capabilities and collaborate with product, engineering, and data teams to implement optimization strategies.
- Design, develop, and maintain dashboards and reporting solutions aligned with key business KPIs, ensuring data accuracy, consistency, and usability.
- Provide leadership with clear visibility into operational performance, trends, and strategic initiatives through effective reporting.
- Deliver ad hoc analyses to support business priorities, collaborate with cross-functional teams, and translate complex analytical findings into clear business recommendations and executive communications.
- Analyze cloud infrastructure utilization and spending patterns to identify cost optimization opportunities, develop monitoring frameworks, and support cost governance initiatives.

Required Qualifications

- Master’s or Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative discipline.
- Minimum of 5 years’ experience in data analytics, business intelligence, data science, or related fields.
- Proficiency in SQL, BigQuery, Hive, Spark, and other data analysis tools.
- Experience with cloud platforms such as Google Cloud, AWS, or Azure.
- Skilled in data visualization tools including Apache Superset, Google Data Studio, Power BI, Tableau, or similar platforms.
- Hands-on experience with analytical programming languages such as Python or R.
- Strong problem-solving, critical thinking, and stakeholder management abilities.

Preferred Qualifications and Benefits

- Expertise in Ontology, Taxonomy, Semantic Web Technologies, and Knowledge Graphs, including ontology design, semantic modeling, metadata management, entity resolution, linked data, graph databases, semantic search, inference engines, and AI-powered knowledge discovery.
- Experience working with Identity Graphs, Customer Identity Resolution, or related data products.
- Familiarity with machine learning, AI/GenAI, and advanced analytics methodologies.
- Knowledge of data governance, data quality frameworks, and managing large-scale data ecosystems.

TransUnion Overview

At TransUnion, we are committed to creating a positive impact through our Workforce for Good initiative, empowering employees to grow, innovate, and contribute to better communities and customer experiences. We foster an environment where associates take charge of their professional development with supportive resources and prioritize work/life flexibility. Join us to work alongside talented professionals, pioneering products, and cutting-edge technology in a culture that values innovation and continuous improvement.

This role offers the opportunity to influence strategic business decisions, enhance operational efficiency through AI-driven solutions, and contribute to the ongoing success and expansion of identity data capabilities globally.