Data Science Manager - Fraud

Talanto

New York, Northern (NY, KY)

Hybrid

USD 140,000 - 200,000

Full time

22 hours ago
Be an early applicant
Application generator

Get a reply from this employer — a resume and cover letter tailored to exactly what they’re hiring for.

Get past ATS filters

Job summary

Talanto is seeking a Data Science Manager to lead a team responsible for customer-facing data science and Fraud product analytics. You will set the team's roadmap, mentor data scientists, and stay involved in analytical methods and investigations.

You will define product metrics, data pipelines, and reporting practices; establish retrospective proofs of concept, identify recurring fraud signals, review designs and code, and collaborate with Product, Engineering, ML, GTM, and customer

Qualifications

  • Proven experience managing and developing data scientists.
  • Deep domain expertise in fraud, risk, or related areas.
  • Strong product analytics, metric design, and measuring product performance.
  • Experience partnering with customers to deliver data-driven insights.

Responsibilities

  • Set a 6–12-month roadmap with Product, Engineering, and GTM, and assign priorities and responsibilities across the team.
  • Define product metrics, their underlying data, and reporting and alerting practices; use results in roadmap and investment decisions.
  • Establish a repeatable process for customer retrospectives and proofs of concept, including data checks, evaluation methods, and clear recommendations.
  • Identify fraud signals and product opportunities that recur across customer analyses and work with Product and MLEs to develop them.
  • Review analytical designs, data models, code, and model evaluations; contribute directly to investigations where your expertise is needed.
  • Coach data scientists through clear expectations, regular feedback, performance discussions, and growth opportunities.
  • Use AI-assisted analysis and development tools where useful, and ensure results are properly reviewed before informing customer recommendations or product decisions.
  • Define how ’s measures, evaluates, and improves the performance of its Fraud products.
  • Apply fraud expertise, product analytics, and customer-facing data science to drive end-to-end product and business impact.
  • Translate customer insights and fraud analyses into scalable product capabilities and opportunities for GTM growth.
  • Lead and develop a high-performing team while remaining technically hands-on with critical analyses and initiatives.
  • Raise the bar for product metrics, analytical rigor, and the data foundations that power decision-making across Fraud.

Skills

Python
SQL
Statistics
Product analytics
Applied modeling
Cross-functional collaboration
Communication

Tools

dbt

Job description

Full time Hybrid New York City Office; Seattle Office; San Francisco HQ

SQL Python Go

Important: if an employer asks you to log into their system via iCloud or Google, send a code, an SMS or Telegram password, run some code, or install software — refuse. These are signs of fraud.

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. powers the tools millions of people rely on to live a healthier financial life. ’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam.

Fraud Data is the data science and machine learning team within ’s Fraud organization, responsible for using data and ML to improve and scale ’s fraud products. Within Fraud Data, the Customer & Product Intelligence team focuses on understanding product performance, uncovering customer insights, and enabling go-to-market teams with data-driven solutions. The team partners closely with customers and GTM teams on fraud analyses and proofs of concept, turning customer learnings into scalable, reusable product capabilities. We also build the metrics, analytics, and data foundations that measure product health, identify opportunities for improvement, and guide product decisions across ’s Fraud portfolio.

As a Data Science Manager, you will lead a team responsible for customer-facing data science and Fraud product analytics. You will set the team's roadmap, develop its data scientists, and remain involved in analytical methods, technical reviews, and customer investigations. You will:

Set a 6–12-month roadmap with Product, Engineering, and GTM, and assign priorities and responsibilities across the team.

Define product metrics, their underlying data, and reporting and alerting practices; use the results in roadmap and investment decisions.

Establish a repeatable process for customer retrospectives and proofs of concept, including data checks, evaluation methods, and clear recommendations.

Identify fraud signals and product opportunities that recur across customer analyses and work with Product and MLEs to develop them.

Review analytical designs, data models, code, and model evaluations; contribute directly to investigations where your expertise is needed.

Coach data scientists through clear expectations, regular feedback, performance discussions, and growth opportunities.

Use AI-assisted analysis and development tools where useful, and ensure results are properly reviewed before informing customer recommendations or product decisions.

Responsibilities

Define how ’s measures, evaluates, and improves the performance of its Fraud products.

Apply fraud expertise, product analytics, and customer-facing data science to drive end-to-end product and business impact.

Translate customer insights and fraud analyses into scalable product capabilities and opportunities for GTM growth.

Lead and develop a high-performing team while remaining technically hands-on with critical analyses and initiatives.

Raise the bar for product metrics, analytical rigor, and the data foundations that power decision-making across Fraud.

Qualifications

Proven experience managing, mentoring, and developing high-performing data scientists.

Deep domain expertise in fraud, risk, or related areas.

Strong experience in product analytics, metric design, and measuring product performance.

Experience partnering directly with customers to deliver data-driven insights and solutions.

Strong technical depth in Python, SQL, statistics, product analytics, and applied modeling.

Demonstrated ability to set technical direction and deliver complex, high-impact initiatives through a team while remaining hands-on.

Excellent communication and cross-functional collaboration skills across Product, Engineering, Machine Learning, GTM, and customer stakeholders.

Nice-to-Have

Experience working with graph-based data or systems to identify fraud patterns and improve model performance.

Experience applying causal inference techniques to complex product or risk problems.

Experience using model interpretability techniques across both traditional machine learning and modern model architectures.

Experience with dbt or similar data transformation and analytics engineering tools.

Our mission at is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to !

is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at .

Please review our Candidate Privacy Notice here.

Additional compensation in the form(s) of equity and/or commission are dependent on the position offered. provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.

Get your free, confidential resume review.
or drag and drop your file here.
Similar jobs

Similar jobs worth comparing

Data Scientist - Fraud
Data Scientist - Fraud

United States Digital Space LLC • United States

Remote
USD 120,000 - 180,000
Equity
Commission
Data Science Manager - Fraud
Data Science Manager - Fraud

Plaid • Seattle (WA)

On-site
USD 216,000 - 329,000
Medical, dental, vision
401(k)
Equity
Senior Machine Learning Engineer - Fraud
Senior Machine Learning Engineer - Fraud

Talanto • San Francisco (CA), Northern (KY)

Hybrid
USD 180,000 - 240,000
Equity
Commission eligible
Medical benefits
+3
Data Science Manager - Fraud
Data Science Manager - Fraud

Plaid Inc • New York (NY)

On-site
USD 150,000 - 190,000
Data Science Manager - Fraud
Data Science Manager - Fraud

Plaid • New York (NY)

On-site
USD 150,000 - 230,000
Equity compensation
Medical, dental, vision
401(k)
Senior Machine Learning Engineer (Research Scientist) - Fraud
Senior Machine Learning Engineer (Research Scientist) - Fraud

Talanto • New York (NY), Northern (KY)

Hybrid
USD 170,000 - 210,000
Senior Machine Learning Engineer - Infra/Ops - Fraud
Senior Machine Learning Engineer - Infra/Ops - Fraud

Talanto • New York (NY), Northern (KY)

Hybrid
USD 105,000 - 215,000
Equity
Commission
Medical benefits
+1
Data Science Manager – Fraud
Data Science Manager – Fraud

Jobtailor • California (MO)

On-site
USD 150,000 - 210,000
Data Scientist - Fraud
Data Scientist - Fraud

Plaid • Seattle (WA)

On-site
USD 176,000 - 227,000
Equity
Commission
Medical plan
+3
Data Scientist - Fraud
Data Scientist - Fraud

Plaid Inc • New York (NY)

On-site
USD 120,000 - 180,000
Equity
Commission
Comprehensive benefits