Senior Analytics Analyst
”TransUnion is committed to finding innovative ways information can be used to help businesses and consumers make smarter decisions.”
-Chris Cartwright, President US Info Services, CEO Administration
What we’ll bring:
- A work environment that encourages collaboration and innovation. We consistently explore new technologies and tools to be agile.
- Flexible time off, workplace flexibility, an environment that welcomes continued professional growth through support of tuition reimbursement, conferences and seminars.
- Our culture encourages our people to hone current skills and build new capabilities, while discovering their genius.
What You’ll Bring:
- A graduate degree in the hard sciences with advanced coursework in statistics
- At least two years of professional analytical modeling experience, solving problems relevant to the problems we solve at TransUnion
- Advanced proficiency with one or more statistical programming languages such as R or SAS;
What we’d prefer to see:
- Additional experience writing intermediate SQL queries for data extraction preferred
Impact you’ll make:
- As an Analyst on our team, you will join a world class group of statisticians, data scientists, mathematicians, and modelers on a mission to extract insights from information and put them to good use. You will have an opportunity to be a part of a variety of analytical projects in a non-siloed environment and be recognized for the work you deliver. TransUnion offers a culture of lifelong learning and as an Analyst here, your growth potential is limitless.
- Collaborate with internal and external partners to deliver innovative analytical products and insights. You will be directly involved in the development of predictive modeling and business intelligence solutions for clients such as credit lenders, insurance carriers, and other financial services institutions.
- Contribute to projects involving descriptive, predictive, and prescriptive analysis leveraging a variety of techniques (such as segmentation, logistic regression, survival analysis, principal component analysis, Monte Carlo simulation, scenario and sensitivity analysis, and machine learning).
- Lead small projects and/ or workstreams as a part of larger projects; this may involve delegating tasks to other team members and managing the team to meet deliverables on time.
- Dig in by extracting data and performing segmentation and statistical analyses on large population datasets (using languages such as R, SAS, SQL, and Python on Linux and PC computing platforms).
- Deliver analytic insights and recommendations in succinct and compelling presentations for internal and external customers at various levels including an executive audience.
- Help to cultivate an environment that promotes excellence, innovation, and a collegial spirit.