Head of Machine Learning

SentiLink

New York (NY)

Hybrid

USD 210,000 - 260,000

Full time

14 days+

Application generator

An application made for this job — a tailored resume and cover letter that speak straight to the posting.

Get past ATS filters

Benefits offered by this job

Employer paid group health insurance

401(k) plan with employer match

Flexible paid time off

Regular company-wide in-person events

Home office stipend

Job summary

A leading fintech company located in New York City is seeking a Head of Machine Learning for Application Fraud. In this role, you will manage a team of data scientists focusing on developing models to detect fraud and improve financial risk products. Ideal candidates should have over 10 years of experience in data science, strong communication abilities, and a proven track record in managing teams. You will also drive project success through technical mentorship and strategy development. The position offers a competitive compensation package and various perks.

Qualifications

10+ years of relevant work experience.
2-5 years of experience managing data scientists.
Strong experience in end-to-end data science development.
Proven track record of solving complex business problems.

Responsibilities

Manage a team of data scientists and grow the team size.
Lead communications with senior leadership and engineering teams.
Develop fraud detection models through the full lifespan.
Research and develop new products around identity verification.

Skills

Data science

Machine learning

Team management

Technical mentorship

Communication

Education

Master's degree or PhD in relevant field

Tools

Python 3

PostgreSQL

AWS

Job description

SentiLink supports a variety of ways to work, ranging from fully remote to in-office. We operate as a digital-first company with strong collaboration across the U.S. and India. We maintain physical offices in Austin, San Francisco, New York City, Seattle, Los Angeles, and Chicago in the U.S., and in Gurugram (Delhi) and Bengaluru in India. If you’re located near one of these offices, we would love for you to spend time in the office regularly. Some roles are hybrid or in-office by design. For example, our engineering team in India works primarily from our Gurugram office.

Role

As Head of Machine Learning, 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 yourself 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.

Requirements

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.

Compensation

$210,000-$260,000/year + equity + benefits

Perks