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Data Scientist

Clevanoo LLC • Contract • San Jose, CA, US • 3d ago

Job Role: Associate Fraud Risk Data Scientist

Duration: 12+Months

Location: San Jose, CA(Hybrid)

Key Job Functions:

Design and develop machine learning and AI models detect/mitigate fraud

Support stakeholders and cross-functional teams in effective usage of models

Drive AI transformation for all risk management activities at BILL

Work with product/engineering to implement, monitor and refine AI solutions and models

Expected Outcomes:

Work closely with team members and stakeholders to consult, design, develop, and manage fraud models and AI solutions.

Utilize data analysis to design and implement fraud models

Collaborate with cross-functional stakeholders including product managers and engineering teams to deploy data-driven fraud models and AI solutions that operate at scale and in real time for end customers.

Make business recommendations to leadership and cross-functional teams with effective presentations of findings at multiple levels of stakeholders.

Development of dashboard and visualizations to track KPI of fraud models implemented

Preferred Skills:

Machine Learning & Artificial Intelligence

Data Science

Model development

Dashboard Creation

Project Management

Strong Communication Skills.

Notes from Hiring Manager:

Strong SQL proficiency

Experience applying statistics and data science to tackle intricate business challenges especially in Fraud mitigation

Proficiency in AWS Quicksight and Tableau

This is a hybrid position, so candidates must be based in the San Jose area. HM will entertain remote candidates if no viable local candidates can be sourced.

Strictly contract to cover multiple leaves over a 1 yr. period.

Potential to extend based on business need and performance.

Day shift: M-F Pacific time

Multiple Zoom interviews (2-3) – SQL assessment during 1st interview.

MUST HAVE:

2-6 years of experience in machine learning/AI, data science, risk analytics & data analysis within relevant industry experience in eCommerce, online payments, user trust/risk/fraud, or investigation/product abuse.

Bachelor’s/Master's degree in Data Science, Data Analytics, Mathematics, Statistics, Data Mining or related field or equivalent practical experience

Experience using statistics and data science (machine learning & AI) to solve complex business problems

Proficiency in SQL, Python, AWS, Excel including key data science libraries

Proficiency in data visualization including Tableau

Experience working with large datasets

Bonus: Experience with development and implementation of AI tools (e.g. LLMs) for risk use cases.