Our Experian Software Solutions Analytics Services Team supports analytic and generative AI products for decisioning analytics and fraud and identity globally.
As a Data Scientist you will use your coding expertise (Python SAS) model risk management and Gen AI experience and analytic consulting skills to lead client and internal engagements for Experians new global product launch and early client success efforts.
This is a remote position. You will report to the VP Applied Fraud Research and Analytics.
Youll have opportunity to:
- Collaborate with Engineering and Data Science teams in the design and implementation of Machine Learning Dashboarding Ad Hoc Analysis and AI applications in a cloud-native big data (AWS) computing platform.
- Lead client analytic consulting engagements with financial services clients including pre-sales and demos training and client success activities to maximize client value. Deliver presentations on analytic results to clients and end-users translating complex findings into actionable insights.
- Partner with Leaders Analytic Consultants Engineers Account Executives Product Managers and external partners to bring new innovative solutions to market that provide impact to Experians broad client base.
- Use Gen AI and model development tools to develop new model document templates and strategies to help clients meet Model Risk Management regulatory requirements.
- Stay informed about regulatory changes technological advancements and model risk management processes to ensure the technology stack meets all compliance requirements.
- Research and integrate new data assets from different sources into Experians ML and AI platform. Develop and assess analytic tools developed internally and externally.
- Gather feedback from internal and external clients to guide new product development feature prioritization and product evolution of tools and capabilities supported by the Ascend Platform.
Qualifications :
- 6 years of experience in analytical roles with experience applying data insights to business problems.
- Advanced degree in Data Science Mathematics Statistics or a related field and a track record for managing complex analytical technology with technologies allowing end-to-end model risk governance including documentation testing approval and monitoring workflows. Understand model risk management regulatory environment and governance requirements for model documentation validation and monitoring.
- Statistical modeling experience using Python or SAS and creating model documentation for Model Risk Management teams in credit or fraud risk and decisioning.
- Experience building analytical tools and providing product and analytic requirements in a regulatory environment.
- Proficiency in at least one programming language (Python or SAS preferred) and familiarity with best coding practices.
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Additional Information :
Benefits/Perks:
Our Experian Software Solutions Analytics Services Team supports analytic and generative AI products for decisioning analytics and fraud and identity globally.As a Data Scientist you will use your coding expertise (Python SAS) model risk management and Gen AI experience and analytic consulting skill...
Our Experian Software Solutions Analytics Services Team supports analytic and generative AI products for decisioning analytics and fraud and identity globally.
As a Data Scientist you will use your coding expertise (Python SAS) model risk management and Gen AI experience and analytic consulting skills to lead client and internal engagements for Experians new global product launch and early client success efforts.
This is a remote position. You will report to the VP Applied Fraud Research and Analytics.
Youll have opportunity to:
- Collaborate with Engineering and Data Science teams in the design and implementation of Machine Learning Dashboarding Ad Hoc Analysis and AI applications in a cloud-native big data (AWS) computing platform.
- Lead client analytic consulting engagements with financial services clients including pre-sales and demos training and client success activities to maximize client value. Deliver presentations on analytic results to clients and end-users translating complex findings into actionable insights.
- Partner with Leaders Analytic Consultants Engineers Account Executives Product Managers and external partners to bring new innovative solutions to market that provide impact to Experians broad client base.
- Use Gen AI and model development tools to develop new model document templates and strategies to help clients meet Model Risk Management regulatory requirements.
- Stay informed about regulatory changes technological advancements and model risk management processes to ensure the technology stack meets all compliance requirements.
- Research and integrate new data assets from different sources into Experians ML and AI platform. Develop and assess analytic tools developed internally and externally.
- Gather feedback from internal and external clients to guide new product development feature prioritization and product evolution of tools and capabilities supported by the Ascend Platform.
Qualifications :
- 6 years of experience in analytical roles with experience applying data insights to business problems.
- Advanced degree in Data Science Mathematics Statistics or a related field and a track record for managing complex analytical technology with technologies allowing end-to-end model risk governance including documentation testing approval and monitoring workflows. Understand model risk management regulatory environment and governance requirements for model documentation validation and monitoring.
- Statistical modeling experience using Python or SAS and creating model documentation for Model Risk Management teams in credit or fraud risk and decisioning.
- Experience building analytical tools and providing product and analytic requirements in a regulatory environment.
- Proficiency in at least one programming language (Python or SAS preferred) and familiarity with best coding practices.
-
Additional Information :
Benefits/Perks:
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