Engineering Manager - Risk Intelligence

  • Mercury - Banking for Startups
  • San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States
  • May 07, 2024

Job Description

In 528 AD, Emperor Justinian I tasked the jurist Tribonian with consolidating the sprawling Roman law into a unified corpus, aiming to streamline governance across the Byzantine Empire. This effort resulted in the Corpus Juris Civilis, a foundational legal system that modernized administration and influenced European legal frameworks profoundly.

At Mercury, we face a challenge similar to the one that inspired Tribonian’s efforts, our organic growth and expansion has created areas where the same data is applied to our systems in differing ways. Similar to how individual jurists' discretion led to different levels of legal certainty in Byzantine Rome, the differences in data definitions we see today prevent our product teams from operating at peak efficiency. Necessitating deeper dives and creating shakier foundations for systemic efforts that we’re striving to fix at a foundational level.

In this role, you will lead a team dedicated to systematizing our approach to data usage in production risk systems, creating a shared understanding of our domain and architecting the systems that empower product teams at Mercury to use our understanding of our customers correctly, responsibly and with applications up-to-and-including real time decision making. Working together with our risk machine-learning team, you will help define a shared understanding of Mercury’s data and establish the systems that make that data foundation accessible to teams across the company.

* Mercury is a financial technology company, not a bank. Banking services provided by Choice Financial Group and Evolve Bank & Trust®; Members FDIC.

As the Engineering Manager for the Risk Intelligence Team, your responsibilities will include:

- Leading a team of talented engineers to develop and refine our understanding of the data we have available and develop a library of shared definitions alongside our own confidence levels that we make available to other product teams.

- Manage the engineering aspects of production data systems needed to deploy machine-learning solutions to combat risk problems.

- Collaborating with Product and Compliance to ensure our solutions not only meet but exceed industry standards in correctness, explainability & sophistication.

- Support engineers who are exploring the gaps in our data infrastructure in developing their intuition of the problem space and crafting an appropriate solution as we build towards self-service production data infrastructure for expert risk operators.

- Embedding the ethos of personalized service into every tool and process your team develops, ensuring that Mercury's data platform provides the guidance that product teams at Mercury need to meet their individual needs without re-visiting definitional discussions anew.

By accepting this mantle, you're not just managing a team; you're playing the part of a leading jurist in establishing an intellectual foundation with long-lasting impact.

In this role, you’ll:

  • Lead a team of ~3-5 engineers.
  • Coach the team to a high level of technical excellence, support them in crafting technical solutions & help them build their knowledge of the fraud & compliance domains.
  • Collaborate with other teams when work overlaps, ideally to achieve a more cohesive product and simpler, more maintainable underlying technical implementation.
  • Balance building new things with maintaining existing systems & work closely with data science and risk analysts to inform the product roadmap.
  • Have the confidence and competence to give feedback to engineers of all skill levels.
  • Create a fulfilling work environment for your team and align their work with their career goals.

You should:

  • Have demonstrated the ability to lead a technical team, with ideally at least 2 years of management experience.
  • Be willing to dive deeply into the domain and help set the direction for the team in collaboration with domain experts and your peers in Data Science & Product Management.
  • Have a strong individual engineering skill set. You will go through roughly the same interview process as our individual contributors, with additional interviews for manager skills.

The ideal candidate for this role has experience building data systems in collaboration with data scientists or analysts, working in a regulated environment or building data platforms at early stage companies and is excited by the opportunity to work through principled product solutions to problems in partnership with experts in compliance & risk management.

We encourage you to try our demo site if you’re interested in applying for the role.

Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidate’s experience, expertise, geographic location, and internal pay equity relative to peers.

Our target new-hire base salary ranges for this role are the following:

  • US employees (any location): $237,600 - $279,500
  • Canadian employees (any location): CAD 216,200 - 254,300

We use Covey as part of our hiring and / or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on January 22, 2024. Please see the independent bias audit report covering our use of Covey here.

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