Lead Data Scientist

About the Role

Brigit's approach to financial services is built on transparency, fairness, and simplicity, aiming to create a brighter financial future for its members. The company has been recognized for its innovative approach, including being named one of the Best Midsize Companies to Work For and Best Startups to Work For by Built In, and one of the Most Innovative Companies by Fast Company. As a Lead Data Scientist, you will be part of a growing team that values autonomy, ownership, and meaningful input from all members.

The data science team at Brigit works closely with cross-functional teams, including engineering, product, and business teams, to ensure that data-driven insights inform all aspects of the company's operations. As a lead in this team, you will have the opportunity to mentor junior data scientists, contribute to the development of best practices in data science, and collaborate on standing up new processes and tools.

What You Will Do

• Develop, test, and deploy new underwriting and risk models to improve the prediction of credit risk and enhance the overall financial health of Brigit's members.
• Build, test, and roll out models related to fraud detection and payment optimization to minimize risk and improve the user experience.
• Contribute to the development of best practices in feature development, model training, and model testing and monitoring.
• Analyze shifts in the customer base as the company grows and identify areas for improvement.
• Collaborate with engineering, product, and business teams to achieve cross-functional goals and ensure that data science insights are integrated into all aspects of the company.
• Mentor junior data scientists and aspiring data scientists across the data team.
• Participate in the development of new data science solutions to address business needs, from ideation to deployment and A/B testing.
• Build end-to-end data science solutions that address specific business challenges and opportunities.
• Work closely with the product team to integrate data science insights into product development.
• Develop and maintain complex SQL queries to extract insights from various data sources.
• Create and manage training datasets, train models, tune hyperparameters, and perform validation and A/B testing.

What We Are Looking For

• Advanced degree in Data Science, Statistics, Computer Science, or a related field.
• 6+ years of experience in data science, with a focus on machine learning and analysis.
• Proven expertise in machine learning principles and techniques, including experience with Python and industry-standard toolkits like sklearn, JupyterLab, pandas, and statsmodels.
• Experience in writing complex SQL queries and the ability to combine multiple data sources.
• Ability to create training datasets, train models, tune hyperparameters, perform validation, and run A/B tests in production.
• Experience in building classification and prediction models, testing them in a startup environment, and iterating to improve their performance.
• Strong written and verbal communication skills, with the ability to explain complex concepts to various audiences.
• Ability to work effectively in a cross-functional team environment, including engineering, product, and business teams.
• Experience in building end-to-end data science solutions to address business needs, from ideation to deployment and A/B testing.
• Strong problem-solving skills, with the ability to operate through ambiguity and learn quickly.

Nice to Have

• Experience with cloud-based data platforms and big data technologies.
• Knowledge of financial services and products, with an understanding of the regulatory environment.
• Experience in mentoring or leading junior data scientists, with a passion for contributing to the growth and development of the team.
• Familiarity with agile development methodologies and version control systems like Git.
• Certification in data science or a related field, demonstrating a commitment to ongoing learning and professional development.

Benefits and Perks

• Competitive salary and benefits package, reflecting the company's commitment to attracting and retaining top talent.
• Opportunity to work remotely, with a stipend for home office setup and ongoing support for remote work arrangements.
• Generous PTO policy, encouraging work-life balance and recognizing the importance of downtime for productivity and well-being.
• Comprehensive health insurance, including medical, dental, and vision coverage, to support the physical and mental health of team members.
• Access to professional development opportunities, including training, workshops, and conference attendance, to support ongoing learning and growth.
• Equity in the company, providing team members with a stake in Brigit's success and a potential long-term financial benefit.
• Recognition and reward programs, celebrating individual and team achievements and reinforcing a culture of excellence and collaboration.

• Ensure your resume and cover letter are tailored to the specific requirements of the Lead Data Scientist role, highlighting your experience with machine learning, Python, and SQL.
• Prepare to discuss your approach to building and deploying machine learning models, including your experience with model training, validation, and A/B testing.
• Be ready to explain complex data science concepts to non-technical stakeholders, demonstrating your ability to communicate insights effectively to various audiences.
• Showcase your ability to work in a fast-paced, agile environment, with experience in collaborating with cross-functional teams to achieve business goals.
• Consider including a portfolio of your work, such as GitHub repositories or research papers, to demonstrate your skills and accomplishments in data science.
• Negotiate your salary based on your experience and the market rate for Lead Data Scientists, and don't hesitate to ask about benefits, equity, and professional development opportunities during the interview process.