Data Scientist, North America Onboarding Team

Austin, TX - USA

Monthly Salary: Not Disclosed

Posted on: 8 hours ago

Vacancies: 1 Vacancy

Job Summary

As a Data Scientist on the North America Onboarding team you will leverage your expertise in data science to innovate and deploy models that ensure regulatory compliance and provide a seamless onboarding experience. Your work will directly influence our ability to mitigate risk while reducing friction for customers opening accounts globally. You will collaborate closely with cross-functional teams including engineering product and risk management.

Design develop and deploy machine learning models to enhance our detection of financial crime compliance violations and risk associated with customer onboarding (KYC) and business verification (KYB).
Take over existing models to prevent chargebacks in North America. Ideate and work on new opportunities with ML to help reduce losses on chargebacks to reduce customer fees.
Analyze large volumes of customer and business data to identify trends patterns and anomalies related to identity verification and regulatory risk typologies.
Design and implement experiments (A/B tests) to evaluate the effectiveness of new risk controls and product features continuously improving performance and balancing compliance with customer experience.
Develop robust data pipelines algorithms and tooling using Python and SQL to support real-time data ingestion and model scoring for the KYC/KYB process.
Collaborate with analysts compliance teams and engineers to translate complex business and regulatory requirements into actionable data insights and automated solutions.
Stay informed about the latest advancements in data science machine learning and regulatory compliance techniques to ensure state-of-the-art capabilities in the risk domain.

Qualifications :

Proven experience in a Data Scientist role ideally with exposure to fraud detection anti-money laundering (AML) or KYC/KYB domains within a FinTech or regulated business environment.
Strong proficiency in machine learning frameworks and Python programming language and are able to make and justify design decisions in your code. You know how to use Git to collaborate with others and are able to review code.
Expertise in data querying languages such as SQL with experience working with large datasets and data processing technologies (e.g. Spark Snowflake).
Familiarity with anomaly detection supervised and unsupervised learning methods and real-time risk scoring and data analysis.
Demonstrated ability to work collaboratively in cross-functional teams and effectively communicate complex technical concepts to non-technical stakeholders.
A strong product mindset with the ability to work independently in a cross-functional and cross-team environment.
Experience with statistical analysis and good presentation skills to drive insight into action.
Strong problem-solving skills with the ability to help refine problem statements and figure out how to solve them.
Familiarity with automating operational processes via technical solutions for example Large Language Models (LLMs)

Additional Information :

For everyone everywhere. Were people building money without borders without judgement or prejudice too. We believe teams are strongest when they are diverse equitable and inclusive.

Were proud to have a truly international team and we celebrate our differences.
Inclusive teams help us live our values and make sure every Wiser feels respected empowered to contribute towards our mission and able to progress in their careers.

If you want to find out more about what its like to work at Wise visit .

Keep up to date with life at Wise by following us on LinkedIn and Instagram.

Remote Work :

Employment Type :

Full-time

Design develop and deploy machine learning models to enhance our detection of financial crime compliance violations and risk associated with customer onboarding (KYC) and business verification (KYB).
Take over existing models to prevent chargebacks in North America. Ideate and work on new opportunities with ML to help reduce losses on chargebacks to reduce customer fees.
Analyze large volumes of customer and business data to identify trends patterns and anomalies related to identity verification and regulatory risk typologies.
Design and implement experiments (A/B tests) to evaluate the effectiveness of new risk controls and product features continuously improving performance and balancing compliance with customer experience.
Develop robust data pipelines algorithms and tooling using Python and SQL to support real-time data ingestion and model scoring for the KYC/KYB process.
Collaborate with analysts compliance teams and engineers to translate complex business and regulatory requirements into actionable data insights and automated solutions.
Stay informed about the latest advancements in data science machine learning and regulatory compliance techniques to ensure state-of-the-art capabilities in the risk domain.

Qualifications :

Proven experience in a Data Scientist role ideally with exposure to fraud detection anti-money laundering (AML) or KYC/KYB domains within a FinTech or regulated business environment.
Strong proficiency in machine learning frameworks and Python programming language and are able to make and justify design decisions in your code. You know how to use Git to collaborate with others and are able to review code.
Expertise in data querying languages such as SQL with experience working with large datasets and data processing technologies (e.g. Spark Snowflake).
Familiarity with anomaly detection supervised and unsupervised learning methods and real-time risk scoring and data analysis.
Demonstrated ability to work collaboratively in cross-functional teams and effectively communicate complex technical concepts to non-technical stakeholders.
A strong product mindset with the ability to work independently in a cross-functional and cross-team environment.
Experience with statistical analysis and good presentation skills to drive insight into action.
Strong problem-solving skills with the ability to help refine problem statements and figure out how to solve them.
Familiarity with automating operational processes via technical solutions for example Large Language Models (LLMs)

Additional Information :

For everyone everywhere. Were people building money without borders without judgement or prejudice too. We believe teams are strongest when they are diverse equitable and inclusive.

If you want to find out more about what its like to work at Wise visit .

Keep up to date with life at Wise by following us on LinkedIn and Instagram.

Remote Work :

Employment Type :

Full-time

Key Skills

Laboratory Experience
Immunoassays
Machine Learning
Biochemistry
Assays
Research Experience
Spectroscopy
Research & Development
cGMP
Cell Culture
Molecular Biology
Data Analysis Skills

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About Company

Wise

Wise is a global technology company, building the best way to move money around the world. With the Wise account people and businesses can hold 40+ currencies, move money between countries and spend money abroad. Large companies and banks use Wise technology too; an entirely new cro ... View more

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