Senior Data Scientist

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What We'll Bring:

At TransUnion, we strive to build an environment where our associates are in the driver’s seat of their professional development, while having access to help along the way. We encourage everyone to pursue passions and take ownership of their careers. With the support of colleagues and mentors, our associates are given the tools needed to get where they want to go. Regardless of job titles, our associates have the opportunity to learn new things and be a leader every day.

Come be a part of our team – you’ll work with great people, pioneering products and cutting-edge technology.

What You'll Bring:

• Graduate degree in statistics, applied mathematics, financial mathematics, computer science, engineering, operations research, or other highly quantitative field; or a bachelor’s degree in a quantitative field with at least three (3) years of relevant professional experience. In either case, the candidate will demonstrate a consistent track record of academic excellence.
• Experience and demonstrated success in client-facing roles over a period of at least one (1) year as well as at least one (1) year of professional experience performing analytic work, preferably in the Financial Services industry.
• Demonstrated interest in industries served by TransUnion, such as financial services, insurance, fraud, and digital marketing (e.g., through relevant internships).
• Strong analytical, critical thinking, and creative problem solving skills.
• Familiarity with and ability to program within and use Spark within an advanced technological framework such as GCP, Databricks or other similar systems; high level of familiarity with Microsoft Office tools.
• Expertise in all areas of Data Science and Predictive modeling with large datasets, ideally including familiarity with some flavors of AI or Deep Learning techniques.
• Versatile interpersonal and communication style with the ability to effectively communicate at multiple levels within and outside the organization; ability to work in a collaborative, fast-paced environment; evidence of initiative-taking.
• Strong project and time management skills with the ability to manage multiple assignments effectively.
• Interest in connecting Data Science to solving business problems around fraud in client-facing consulting roles.
• Ability to travel up to 20%.

What Love to See:

• Proven ability to operate effectively under modest supervision in a complex and dynamic, matrixed environment.
• Familiarity with credit bureau data and solutions.
• Familiarity with fraud particularly as it pertains to financial services or telecommunications industries.

Impact You'll Make:

This position is responsible for supporting the development of analytic solutions through consulting engagements for TransUnion’s clients primarily for fraud prevention but potentially across a broader array of applications including credit, insurance and marketing business applications. This position requires a general understanding of US financial services risk management practices and credit bureau data and solutions. Relevant aspects include how credit data are reported to credit bureaus, how credit data are leveraged for risk solutions, and some understanding of the relevancy of that data to fraud prevention within financial services. Additionally, a successful candidate will bring a perspective into how addressing fraud within the financial services industry might be broadened into other industries such as telecommunications.

• You will partner with internal and external cross-functional teams to drive new business initiatives and deliver long term value-added solutions to various TransUnion customers. These tasks will include –among others- the development of predictive models and business intelligence solutions of moderate scope and complexity for individual customers within the various industries served by TransUnion.
• You will lead analytic client engagements involving descriptive, predictive, and prescriptive analysis, primarily for fraud business cases leveraging multiple analytic techniques with an emphasis on, but not limited to, predictive modeling and strategies for the concurrent use of multiple solutions. As a project leader, you will take ownership of analytic aspects of the project from design, to