Lead Data Scientist, Financial Services Consulting

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Team Overview

At Trans Union, this team reports to a Director of Data Science & Analytics, playing an integral role by working end-to-end with financial services clients, fostering consultative relationships that enable them to deliver impactful solutions. This team specializes in building both custom and generic models tailored to each client's unique needs, ensuring that every engagement is as effective as possible. This is a hybrid position and involves regular performance of job responsibilities virtually as well as in-person at an assigned TU office location for a minimum of two days a week.

Role Overview and Core Responsibilities

• You will partner with internal and external cross-functional teams to drive new business initiatives and deliver long term value-added product propositions for B2B customers in the US financial services segment s includes but is not limited to the development of predictive risk management and business intelligence solutions for credit card issuers, auto & mortgage lenders, collections agencies and retail banks.
• You will lead analytic client engagements involving descriptive, predictive, and prescriptive analysis through the consumer lending portfolio lifecycle, leveraging a variety of techniques (e.g., segmentation, logistic regression, survival analysis, principal component analysis, Monte Carlo simulation, scenario and sensitivity analysis).
• You will design and write programs for data extraction, segmentation and statistical analysis on large population datasets using languages such as R, Python, SQL, Hive, and Pig on Linux, PC, and mainframe computing platforms.
• You will deliver analytic insights and recommendations in succinct and compelling presentations for internal and external customers and an executive audience.
• You will develop project proposals, sales presentations and promotional collateral to enable the adoption of integrated customer solutions supported by Trans Union.
• You will identify strategies and opportunities for customers to test and adopt Trans Union's analytic products and services.
• You will provide mentorship and training to junior colleagues and maintain progress on all initiatives under limited direct supervision.
• You will foster a high performance culture and cultivate an environment that promotes excellence and reflects the Trans Union brand.

Required Knowledge and Experiences

• Bachelors (4 year) degree in statistics, applied mathematics, financial mathematics, engineering, operations research, or another highly quantitative field.
• 7+ years of professional experience performing analytic work in Financial Services, consumer credit, or a related industry
• Strong analytical, critical thinking, and creative problem-solving skills
• Advanced programming skills; proficiency with R/Python and SQL; experience using other programming and data manipulation languages preferred (Hive, Pig, C/C++, Java); high level of familiarity with Microsoft Office tools
• 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
• Strong project management skills with the ability to manage multiple assignments effectively
• Ability to travel 10-20%

We're also looking for the preferred skills below. Whether you are proficient or could use some brushing up, we're happy to support your career development and growth in:

• Master's or PhD degree in statistics, applied mathematics, financial mathematics, engineering, operations research, or another highly quantitative field. And, at least two (2) years of professional experience performing advanced analytic work in Financial Services, consumer credit, or a related industry
• Familiarity with credit bureau data and business practices
• Experienced in managing full life cycle of credit risk models and look alike models for consumer financial services industry, including model design, development, and deployment, monitoring, and validation
• Operates independently in a complex and dynamic, matrixed environment
• Experien…