Data Scientist for Insurance Analytics
What We'll Bring:
At TransUnion, we have a welcoming and energetic environment that encourages collaboration and innovation – we’re consistently exploring new technologies and tools to be agile. This environment gives our people the opportunity to hone current skills and build new capabilities, while discovering their genius.
Come be a part of our team – you’ll work with great people, pioneering products and cutting-edge technology.
What You'll Bring:
- You come in with 1-2 years of professional statistical modeling experience with solid knowledge of GLM, Machine Learning, AI etc. and proficient in programming SAS, R, Python, Hive etc.
- You have strong written and verbal communication skills with the ability to clearly articulate ideas to both technical and non-technical audiences
- You have robust analytical, critical thinking, and creative problem solving skills with prior exposure to solving problems relevant to the problems we solve at TransUnion through either academic research or field experience
- Your strong project management and time management skills including the ability to prioritize and contribute to multiple assignments simultaneously, delegating work when necessary, setting clear goals, and managing customer expectations
- You have an advanced degree in fields of quantitative discipline such as Mathematics, Statistics, Engineering, Analytics and other related fields with advanced coursework in statistics
What we love to see:
- You have hands on experience in optimization of machine learning algorithm and experience in suing deep learning algorithm
- Advanced proficiency with one or more statistical programming languages such as R or SAS; additional experience writing intermediate SQL queries for data extraction is even better
- Ph. D. degree in statistics/computer science from a highly accredited university
Impact You'll Make:
- Contribute to advanced insurance analytics on topics including utilizing telematics data for risk differentiation, as well as other insurance IoT.
- Participate insurance analytics tool development projects.
- 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 work streams 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).
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.