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7 дней назад

Data Science Manager (Fraud)

216 000 - 329 000$
Формат работы
hybrid
Тип работы
fulltime
Страна
US
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Описание вакансии

TL;DR
Data Science Manager (Fraud) (Data Science/Fraud Analytics): Leading customer-facing fraud data science and product analytics initiatives with an accent on roadmap planning, metric design, customer insights, and applied modeling. Focus on translating fraud analyses into scalable product capabilities, reviewing analytical work and model evaluations, and coaching a high-performing data science team.

Data Science Manager Fraud

Company

Plaid Inc.

Conditions

1 day ago Salary: 216K - 329K

Skills

Candidate Availability

Required and preferred rules are kept separate and reflect the wording in the original posting.

About the Role

You will lead customer-facing data science and fraud product analytics. You will set the team's roadmap, define metrics and reporting practices, establish customer-analysis processes, identify product opportunities, review analytical work, investigate critical issues, and coach data scientists.

Requirements

  • Experience managing, mentoring, and developing data scientists.
  • Deep expertise in fraud, risk, or related domains.
  • Experience in product analytics, metric design, and measuring product performance.
  • Experience partnering directly with customers on data-driven insights and solutions.
  • Technical depth in Python, SQL, statistics, product analytics, and applied modeling.
  • Ability to set technical direction and deliver complex initiatives through a team while remaining hands-on.
  • Communication and cross-functional collaboration skills.

Responsibilities

  • Set a 6–12-month roadmap with Product, Engineering, and GTM.
  • Define product metrics, underlying data, reporting, and alerting practices.
  • Establish repeatable processes for customer retrospectives and proofs of concept.
  • Identify recurring fraud signals and product opportunities.
  • Review analytical designs, data models, code, and model evaluations.
  • Contribute directly to critical customer investigations.
  • Coach data scientists through feedback, performance discussions, and growth opportunities.
  • Define, evaluate, and improve Fraud product performance.
  • Translate customer insights and fraud analyses into scalable product capabilities.
  • Lead and develop a high-performing team.

Benefits

  • Equity and/or commission
  • Medical insurance
  • Dental insurance
  • Vision insurance
  • 401(k)

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