Predictive Modeling Analyst - Insurance
”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.
- 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.
What you’ll bring:
- Master’s or PhD degree in statistics, applied mathematics, engineering, operations research, or another highly quantitative field with a track record of academic excellence.
- Demonstrated interest in Financial Service, Insurance, or relevant industries.
- Advanced programming skills; proficiency with a statistical language such as R, Python, or SAS
- Strong project management skills with the ability to manage multiple assignments effectively.
What we’d prefer to see:
- Experience in the Insurance industry
- Previous experience in using other programming and data manipulation languages preferred (SQL, Hive, Pig, Python, C/C++, Java, VBA)
- Experience working with credit bureau data and solutions preferred.
- Aptitude and interest in client-facing roles.
Impact you’ll make:
- 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).
- 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 and innovation
We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability status, veteran status, marital status, citizenship status, sexual orientation, gender identity or any other characteristic protected by law.