Data Science Manager - Application Fraud

Role Description

As a Data Science Manager for Application Fraud at SentiLink, you will directly manage a team of talented data scientists that build our suite of products: models that identify fraudsters and also advance our growing suite of products in financial risk. In this capacity, you will be relied upon to be a technical leader, mentor, and owner of your respective domain, both for your own team and the organization.

• Utilize your abilities as a strong data scientist to mentor your team, probe their understanding, and challenge them to do their best work.
• Your team will often work on projects with high visibility and impact that require deep domain understanding, critical thinking, and strong technical abilities.
• This role requires managing full-stack data scientists, whose work involves model development, analysis, and writing production code.
• You should share that same skillset and be interested in having end-to-end ownership in a fast-moving environment where deep domain understanding drives development and unusual insights drive our competitive advantage rather than optimization of new machine learning methodologies.

Technologies: Python 3, PostgreSQL, and AWS infrastructure (EC2, S3, RDS, Redshift, etc.)

Responsibilities

• Directly manage a team of highly skilled data scientists. Start from 2-3 and grow to 5-6.
• Act as a technical mentor that can dive deep and provide detailed direction.
• Lead planning, resourcing, and communications with senior leadership, product, and engineering teams.
• Develop strong business intuition and guide your team to deliver performant DS solutions on aggressive timelines.
• Develop and maintain SentiLink’s fraud detection models through the full model development lifespan: from data acquisition decisions through featurization, focusing labeling resources, model training, experimentation, productionalization, and monitoring.
• Research new types of fraud and develop new SentiLink products around identity verification.
• Achieve success by researching/developing through iteration, integration of new data sources, and inventive feature engineering.
• Write production-ready code that can be relied on for real-time decision making by our partners.
• Design, perform, and present analyses that will inform data acquisition, product development, risk operations priorities, marketing, and sales efforts.

Qualifications

• 10+ years relevant work experience & relevant Masters or 7+ years & relevant PhD.
• 2-5 years experience directly managing a team of data scientists, ideally in a startup environment.
• 3+ years of startup experience.
• Excellent communicator and team player.
• Proven track record of solving complex/high profile business problems with DS/ML solutions.
• Experience in communicating outcomes/progress to senior management/stakeholders.
• Very strong in “end to end” DS development: Planning, fleshing out success criteria/metrics, getting buy-in, developing the solution, delivering the solution (prod/deck/strategy doc/etc).
• Strong practical ML/Stats knowledge, i.e. can easily employ the suite of standard ML/stats tools to quickly scope out solutions, and double down where needed. Experience with SOTA ML solutions is a plus.
• Interest in developing deep domain expertise for product-focused work: a background in fraud is not required, but willingness to learn is.
• Experience writing production code and tests.
• Detail oriented and thoughtful—someone we can rely on to make business-changing decisions.
• Thrive in a fast-paced environment characterized by the need to solve extremely varied, high impact, open-ended problems.
• Bonus for familiarity with: identity solutions, fintech, or adjacent industries.
• Candidates must be legally authorized to work in the United States and must live in the United States.

Requirements

• Compensation: $210,000-$260,000/year + equity + benefits

Benefits

• Employer paid group health insurance for you and your dependents
• 401(k) plan with employer match (or equivalent for non US-based roles)
• Flexible paid time off
• Regular company-wide in-person events
• Home office stipend, and more!

Corporate Values

• Follow Through
• Deep Understanding
• Whatever It Takes
• Do Something Smart