Remote Associate Fraud Risk Data Scientist

JOB DESCRIPTION: We are looking for a talented, enthusiastic and dedicated person to support the Fraud Risk Data Science Team within the Risk Data & AI Innovation Org. The incumbent will be responsible for supporting key projects associated with fraud detection, risk analysis and loss mitigation. This position requires a person who has experience with machine learning, model development with cutting edge AI/ML frameworks, performing analytics, statistical analysis and model monitoring. Experience with LLMs and other AI tools would be a big plus. Wed love to chat if you 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. • Bachelors/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 • Ability to clearly communicate complex results to technical experts, business partners, and executives including development of dashboards and visualizations, ie Tableau. • Comfortable with ambiguity and yet able to steer AI and machine learning projects toward clear business goals, testable hypotheses, and action-oriented outcomes • Demonstrated analytical thinking through data-driven decisions, as well as the technical know-how, and ability to work with your team to make a big impact. • Desirable to have experience or aptitude solving problems related to risk using data science and analytics • Bonus: Experience with development and implementation of AI tools (e.g. LLMs) for risk use cases. 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. • Bachelors/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.