Associate Data Scientist (fraud Strategy)

Associate Data Scientist (Fraud Strategy) Job Type: Contract Contract Length: 1 year Target Start Date: ASAP Work Location/Structure: San Jose, CA (Hybrid) About the Opportunity Our client, a leader in financial automation software, is looking for a talented, enthusiastic, and dedicated Associate Data Scientist to support their Fraud Risk Strategy team. This role is responsible for supporting key projects associated with fraud detection, risk analysis, and loss mitigation. This position requires a person who has experience with performing analytics, refining risk strategies, and developing predictive algorithms, preferably in the risk domain. This is a high-impact role that requires a self-motivated professional who can hit the ground running and deliver results quickly. Key Responsibilities & Deliverables Design rules to detect/mitigate fraud. Develop Python scripts and models that support fraud strategies. Investigate novel/large fraud cases and identify root causes. Set strategy for different risk types. Work with product/engineering to improve control capabilities. Develop and present strategies and guide execution. Work closely with team members and stakeholders to consult, design, develop, and manage fraud strategies and rules that solve emerging fraud trends and provide a great experience to end customers. Utilize data analysis to design and implement fraud strategies. Collaborate with cross-functional stakeholders including product managers and engineering teams to deploy data-driven fraud 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. Develop dashboards and visualizations to track KPI of fraud strategies implemented. Required Skills & Experience Maximum 2 years of experience in risk analytics, data analysis, and data science within relevant industry experience in eCommerce, online payments, user trust/risk/fraud, or investigation/product abuse. Bachelor’s degree in Data Analytics, Data Science, Mathematics, Statistics, Data Mining, or a related field, or equivalent practical experience. Experience using statistics and data science to solve complex business problems. Proficiency in SQL, Python, Excel (including key data science libraries), and data visualization (including Tableau). Experience working with large datasets. Ability to clearly communicate complex results to technical experts, business partners, and executives, including the development of dashboards and visualizations. 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 AWS, knowledge of fraud investigations, payment rule systems, working with ML teams, and fraud typologies. Strong communication and project management skills. #J-18808-Ljbffr