View on Remote OK
Roles
Compensation
USD 185000 - 215000
Anticipated annual base salary $185,000 - $215,000 plus 10% annual bonus opportunity; plus benefits including medical, dental, vision insurance, flexible PTO, 401k plan, paid parental leave, Wellhub and Headspace, monthly wifi/cell reimbursements, and annual Learning & Development reimbursement.
- Salary period
- yearly
- Location basis
- San Francisco (location listed)
- Bonus
- 10% annual bonus opportunity
Benefits
- Medical, dental, and vision insurance
- Flexible PTO Policy
- 401k plan
- Paid Parental Leave
- Physical and mental wellbeing benefits including Wellhub for access to virtual workouts and discounted gym memberships
- Headspace for covered virtual therapy sessions and unlimited on demand health support
- Monthly reimbursements to use against wifi and cell phone bills
- Annual reimbursement for Learning & Development
Tech stack
Required
Location
San Francisco
Work setup
- Employment
- full-time
- Level
- Senior
- Remote policy
- Remote OK; Work arrangement: Remote. No specific timezone requirements stated.
- Remote scope
- country-limited
- Authorization
- Brigit uses E-Verify for employment authorization.
Role details
Responsibilities
- Build, test and roll out new underwriting and risk models to better predict risk
- Own the full modeling lifecycle from conception through to production
- Build, test and roll out new or improved models related to fraud and payments
- Contribute to building best practices for feature development, model training and model testing and monitoring
- Analyze how the customer base is shifting as the company grows and pinpoint areas to improve
- Help existing engineering and business teams achieve cross-functional goals
- Mentor more junior data scientists or aspiring data scientists across the data team
Requirements
- 6+ years of experience doing data science (modeling + analysis)
- Advanced degree in data science, statistics, computer science, or related field
- Proven expertise in machine learning principles and techniques
- Experience in Python
- Experience using industry-standard modeling toolkits like scikit-learn, JupyterLab, pandas, matplotlib, statsmodels
- Experience in writing complex SQL queries and ability to put together multiple data sources
- Experience creating training data sets and training models
- Experience tuning hyperparameters
- Experience performing validation
- Experience running A/B tests in production
- Experience creating and owning performance and model monitoring
- Experience building classification and prediction models
- Ability to test and iterate models in a startup environment
- Ability to work effectively and communicate ideas/code clearly in a cross functional team environment (Engineering, Product and Business teams)
- Ability to work end-to-end from ideation to deployment and A/B testing
- Strong written and verbal communication skills
Application
Please mention the word **MIGHTILY** and tag RMTM4LjIwMS4xMjYuMTgx when applying to show you read the job post completely (#RMTM4LjIwMS4xMjYuMTgx).
- Portfolio
- not required
- GitHub
- unclear
- Cover letter
- unclear
- Apply flow
- external
Company context
Help hard working Americans build a brighter financial future.
- Product
- Financial health company providing transparent, fair, simple financial products and services to help members build credit quickly
- Industry
- Finance
- Stage
- high-growth
Contact
accommodations@hellobrigit.com
Description
Hi, we're Brigit! A holistic financial health company helping everyday Americans build a brighter financial future. As a Data Scientist on our team you’ll be responsible for building, improving and maintaining the key ML models that enable our services. Key problem spaces include identifying credit risk, identifying fraud early, and optimizing transaction timing to avoid overdraws. Role Overview: Build, test and roll out new underwriting and risk models; own the full modeling lifecycle from conception through production; build, test and roll out models related to fraud and payments; contribute to best practices for feature development, model training and model testing and monitoring; analyze how customer base is shifting and pinpoint improvements; help engineering and business teams achieve cross-functional goals; mentor more junior data scientists. What you have: 6+ years of experience doing data science (modeling + analysis); advanced degree in data science, statistics, computer science, or related; proven expertise in machine learning principles; experience in Python using sklearn, JupyterLab, pandas, matplotlib, statsmodels; experience writing complex SQL queries; creating training data sets, training models, tuning hyperparameters, validation, running A/B tests in production, performance and model monitoring; building classification and prediction models and iterating in a startup environment; ability to communicate clearly cross-functionally; strong written and verbal communication. Benefits: Medical, dental, and vision insurance; Flexible PTO; 401k plan; Paid Parental Leave; physical and mental wellbeing benefits including Wellhub and Headspace; monthly reimbursements to use against wifi and cell phone bills; annual reimbursement for Learning & Development; high-growth company and dynamic, flexible, collaborative start-up work environment.
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