Sr. Consultant, Data Science & Analytics

Trans Union’s Job Applicant Privacy Notice

Team Overview

At Trans Union, we are dedicated to finding ways information can be used to help people make better and smarter decisions. As a trusted provider of global information solutions, our mission is to help people around the world access the opportunities that lead to a higher quality of life, by helping organizations optimize their risk-based decisions and enabling consumers to understand and manage their personal information.

Because when people have access to more complete and multidimensional information, they can make more informed decisions and achieve great things.

Every day Trans Union offers our employees the tools and resources they need to find ways information can be used in diverse ways. Whether it is helping businesses better manage risk, providing better insights so a consumer can qualify for his first mortgage or working with law enforcement to make neighborhoods safer, we are improving the quality of life for individuals, families, communities and local economies around the world.

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

The duties and responsibilities described above are the essential functions of the job. The qualifications below are representative of the knowledge, skills, and/or abilities required.

• 5+ years of relevant experience in credit, financial services consulting, or financial services industry
• Bachelor’s degree or higher in compute science, mathematics or statistics. Master’s Degree preferred.
• Familiar with various statistical, econometric, and quantitative analysis techniques and their applicability to business problems
• Proficiency in the use of a statistical software application, for example SAS, R, XENO
• Advanced technical capability, for example Excel, SAS, SQL etc.
• Experience in developing statistical models is an asset
  - Research, develop, test, and document methodologies/models, procedures and related processes for credit risk measures (e.g. probability of default, exposure at default, loss given default)
• Model implementation
  - Liaise with other stakeholders to facilitate model approval and implementation; participate in formulating implementation requirements, and conducting pre-implementation testing.
• Evidence of strong analytical, critical, and creative thinking and willingness to take initiative in problem-solving.
• Excellent communication skills (oral & written) with ability to communicate complex concepts and solutions successfully to all levels of management and technical expertise.
• Must have proven ability to interact and mediate with all levels of organization, from most junior to most senior, from all aspects of business including technical and operational.
• Proven ability to mediate through complex business issues from multiple points of view and levels of organization – while achieving desired outcome
• Track record of independent self-motivated results. Must also be able to work effectively under minimum supervision.
• Willingness and ability consistently assert point of view in a non-confrontational manner.
• Capable of translating market/economics trends into tangible product concepts/ideas or solutions
• In-depth understanding of credit reporting industry preferred
• Direct experience in developing and/or designing statistical/econometric or comparable modeled solutions and/or similar empirical analyses.
• Project and/or process management experience highly desirable
• In-depth knowledge of tools, software and technology platforms available in the marketplace; direct experience in use of competitive offerings desired
• Knowledge and/or direct experience with integrating solutions into client systems or business processes
• Well rounded experience consulting or supporting intangible solutions
• Advanced Experience in using cloud-based tools and technologies to extract insights from data, focusing on areas like data preparation, model building, and deploying machine learning solutions within a cloud environment
• Must have proven ability to show working in both…