Data Scientist

Salary: $67,500 - 112,500 per year Requirements: We require a masters degree or PhD in Statistics, Applied Mathematics, Financial Mathematics, Computer Science, Engineering, Operations Research, or another highly quantitative discipline. We require at least 1 year of experience in analytics, data science, statistical modeling, or quantitative analysis. We need an understanding of U.S. financial services risk management practices and how data-driven insights inform business decisions. We value experience in financial services, insurance, fraud, credit risk, digital marketing, or related sectors. We require proficiency in Python or R for statistical analysis, predictive modeling, and data science solution development. We require SQL skills for data extraction, transformation, segmentation, and analysis. We need experience working with large datasets and distributed data platforms such as Hive and Spark. We expect knowledge of machine learning, predictive analytics, statistical modeling, and business intelligence methods. Preferred experience includes working with credit bureau data, credit risk models, or financial services analytics. Preferred exposure includes programming languages such as Java or C/C++. Preferred background includes client-facing consulting or analytics advisory work. Preferred knowledge includes fraud analytics, insurance analytics, or marketing analytics solutions. Responsibilities: We develop predictive models and advanced analytics solutions for clients across credit risk, fraud, insurance, and marketing use cases. We lead analytics engagements from project design and development through implementation, validation, and client presentations. We partner with internal stakeholders, sales teams, and external clients to uncover opportunities where data science can create business value. We perform descriptive, predictive, and prescriptive analyses to address complex customer business challenges. We translate analytical findings into practical business recommendations and present results to both technical and non-technical audiences. We design, build, and optimize data extraction, segmentation, and statistical analysis workflows using large-scale datasets. We create repeatable analytical frameworks and process improvements that enhance efficiency and scalability. We support business development through project proposals, client presentations, and analytic consulting. We are expected to follow company policies, use sound judgment, act trustworthily, work safely, communicate respectfully, and safeguard business operations, confidential information, and our reputation. Technologies: Business Intelligence Hive Support Java Machine Learning Marketing Python SQL Spark More: We are collaborating with hackajob to connect us with exceptional professionals for this role. Our Financial Services Analytics team partners with banks, lenders, insurers, and other financial institutions to solve complex business challenges using advanced analytics and TransUnion data assets. We deliver predictive modeling, risk analytics, fraud solutions, and business intelligence insights that help clients make smarter decisions and drive measurable outcomes. This is a hybrid role with regular virtual work and in-person presence at an assigned TransUnion office location for at least two days each week. We offer a broad benefits package designed to support health, protection, family, future, personal growth, and wellness from day one, including medical, dental, and vision coverage, retirement savings support, paid time off, tuition reimbursement, and well-being resources. We are committed to diversity, inclusion, work/life flexibility, and creating a positive impact through our Workforce for Good. last updated 37 week of 2026