Credit Strategy Data ScientistSan Jose, California, United StatesAbout the Job Credit Strategy Data ScientistWe are looking for a talented, enthusiastic and dedicated person to join the Credit Risk Strategy team. The incumbent will be responsible for leading key projects associated with credit risk assessment, data analysis and loss mitigation. This position requires a person who has experience performing analytics, refining risk strategies, and developing predictive algorithms preferably in the credit risk domain.Key Job FunctionsDesign rules to detect/mitigate lossInvestigate novel/large casesIdentify root causeSet strategy for different risk typesWork with product/engineering to improvement control capabilitiesDevelop and present strategies and guide executionDrive results that maximize eligible customers while controlling lossesProfessional Experience/Background to be Successful in This RoleMinimum 2 years of experience in risk analytics, data analysis, or data science within the Fintech or online payments industry.Bachelors degree in computer science, Engineering, Mathematics, Statistics, Data Mining or 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.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 analytics 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 AWS, payment rule systems, and knowledge of credit products.Expected Outcome in 6-12 MonthsDevelopment of dashboard and visualizations to track KPI of credit strategies implementedWork closely with team members and stakeholders to consult, design, develop, and manage credit trends and losses that not only solve emerging loss trends but also provide a great experience to end customers.Utilize data analysis to design and implement credit strategiesAnalyze and transform data using RaaS platforms to identify loss patterns and optimize the systems to flag these patternsCollaborate with cross-functional stakeholders including product managers and engineering teams to deploy data-driven credit 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.Preferred SkillsData analyticsRule developmentDashboard CreationProject ManagementStrong CommunicationNotes from Hiring ManagerInterview process: Multiple (At home screening, 1 technical interview with senior team member, 1 interview panel with hiring manager and team member).Team size: 5 team members, position will work closely with a senior team member at outset, role will largely focus on reporting, so experience with visualization and data storytelling is a plus.Must HaveBachelors degree in computer science, Engineering, Mathematics, Statistics, Data Mining or related field or equivalent practical experience.Minimum 2 years of experience in risk analytics, data analysis, or data science within the Fintech or online payments industry.Experience using statistics and data science to solve complex business problems.Proficiency in SQL, Python, Excel including key data science libraries.Experience working with large datasets.Ability to clearly communicate complex results to technical experts, business partners, and executives including development of dashboards and visualizations, i.e.
Tableau.Desirable to have experience or aptitude solving problems related to risk using data science and analytics.Experience with AWS, payment rule systems, and knowledge of credit products.