Company Name: PatientFi

Job Details: Hiring,Remotely,in,United,States,Remote,Junior

Job Url: https://builtin.com/job/data-scientist/8169010

Job Description: Company DescriptionPatientFi® is a technology-based, point-of-sale financing company in Irvine, CA that partners with healthcare providers to offer patients a friendly payment solution for out-of-pocket medical and dental procedures. The company serves various healthcare specialties, including plastic surgery, dermatology, ophthalmology, dentistry, fertility, and medical spas. PatientFi's mission is to expand patient access to elective healthcare treatments by removing the cost barrier and providing patients with a convenient payment option.Job Description / ResponsibilitiesAs a Data Scientist at PatientFi, you will play a key role in developing industry-leading machine learning models for managing credit and fraud risks. You will work with multiple complex data sources, such as credit bureau reports and customer-supplied information, to optimize underwriting decisions, approve/decline strategies, credit line assignments, and fraud detection methodologies.Key responsibilities include:Develop and implement machine learning models for credit risk assessment and fraud detection, ensuring compliance with lending best practices and regulatory requirementsBuild and improve quantitative and qualitative models (including CECL, Prepayment, Weighted Average Remaining Maturity (WARM), Probability of Default and Loss Given Default (PD/LGD) methodologies)Leverage advanced data analytics to dynamically segment applicants and loans based on behavior and performanceOptimize risk-based pricing strategies, underwriting criteria, and collections strategies using data-driven insightsCollaborate with engineers to deploy machine learning models into production environmentsMonitor, analyze, and report on model performance, ensuring continual refinement and adaptation to changing market conditionsDevelop LookML and SQL queries to build dashboards in Looker for tracking model and business performanceExtract the most value from data to drive key business metrics and enhance risk management strategiesConduct ad-hoc analysis to support risk management, investor services, operations, and corporate developmentSupport analysis and reporting in stress testing modelsDesired Skills / Experience1+ years of experience in Data Science, Credit Risk, Fraud Risk, Quantitative Analytics, or related fieldsAdvanced degree (M.S./PhD preferred) in Statistics, Computer Science, Engineering, Economics, or a related quantitative field1+ years of relevant experience within consumer credit risk management, ideally at a FinTech startup, banking or lending company; bonus points for healthcare experience Expertise in Python and SQL, with a strong understanding of coding best practices and model documentationExperience implementing data pipelines using Google Cloud products (BigQuery, GCS, Cloud DataFlow, Cloud Pub/Sub, Cloud BigTable)Understanding of data warehousing concepts, data engineering, and data modelingStrong experience in risk modeling, fraud detection, and machine learning techniques applied to financial services.Strong communication and interpersonal skills, with the ability to clearly translate technical insights to business stakeholdersSelf-motivated, results-oriented, and capable of managing multiple projects in a fast-paced environmentExperience working with Looker (or similar BI tools like Tableau, Power BI) to design reports/dashboardsFamiliarity with bureau data and alternative data sources for credit and fraud risk analysisKnowledge of cash flow modeling and loss forecasting is a plus