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Equifax · 2 days ago

Data Scientist, Model Risk Management

Alpharetta, GA

Full-time

Hybrid

Senior Level

5+ years exp

Equifax is looking for a Data Scientist, Model Risk Management to join their world-class Model Risk Management team. In this role, you will conduct model validation across various Risk, Fraud, and Generative AI applications while ensuring high-quality solutions and communicating critical results with partners across the organization.

AnalyticsConsultingDatabase

No H1B

Responsibilities

Conduct model validation to verify quality of models and identify data anomalies using statistical and advanced machine learning approaches

Apply critical rigor and assess models built for various verticals including retail banking, auto lending, communications and utilities, mortgage, and payments

Research new and advanced data science techniques as appropriate for a specific solution

Be able to learn quickly and conduct research and exploration independently on new modeling techniques; Keep him/herself up to date to the latest in the industry

Must be proficient in Python and SQL and have sufficient knowledge in such advanced computational languages/applications as Big Query, TensorFlow, Scala, SAS, and/or R

Be able to communicate concisely in both written and oral English and to create model validation reports, including presentation to senior management, supervisory authorities, and model stakeholders

Must be a great team player

Must be self-motivated, disciplined and task focused; Be able to deliver high quality results within strict deadlines

Qualification

PythonSQLStatistical modelingMachine learningData validationDeep Neural NetworksGenerative AIAnalytical skillsCloud knowledgeUNIX environmentTeam playerSelf-motivatedCommunication skillsProblem solving

Required

Conduct model validation to verify quality of models and identify data anomalies using statistical and advanced machine learning approaches

Apply critical rigor and assess models built for various verticals including retail banking, auto lending, communications and utilities, mortgage, and payments

Research new and advanced data science techniques as appropriate for a specific solution

Be able to learn quickly and conduct research and exploration independently on new modeling techniques; Keep him/herself up to date to the latest in the industry

Must be proficient in Python and SQL and have sufficient knowledge in such advanced computational languages/applications as Big Query, TensorFlow, Scala, SAS, and/or R

Be able to communicate concisely in both written and oral English and to create model validation reports, including presentation to senior management, supervisory authorities, and model stakeholders

Must be a great team player

Must be self-motivated, disciplined and task focused; Be able to deliver high quality results within strict deadlines

5 - 7 years of professional experience as a data scientist or statistical modeler in at least one of the following: identity and fraud, credit risk, telecommunications, financial services, payment, ecommerce, B2B or B2C, marketing, insurance, or security analytics arena

Bachelor's degree or higher in Data Science, Computer Science, Mathematics, Engineering, Operations Research, Statistics or other related discipline

Strong quantitative analytical experience, including hands-on and background in using statistics, regression modeling, neural networks, decision trees, random forest, support vector machine, kernel based methods, clustering and similar methods