Senior Data Scientist, Fraud Machine Learning

Posted 2 Days Ago
Be an Early Applicant
Hiring Remotely in US
Remote
Mid level
eCommerce • Insurance • Software
The Role
As a Senior Data Scientist in Fraud Machine Learning at Extend, you'll develop technologies and strategies for detecting claim fraud across various products. Responsibilities include building and deploying machine learning models, monitoring their performance, and collaborating with cross-functional teams to enhance fraud prevention efforts.
Summary Generated by Built In

About Extend:

Extend is modernizing the $100 billion-per-year protection plan industry using cutting-edge technology and top-notch customer service. 

Our technology-forward omnichannel and API-first solution allows any merchant to offer protection plans, both online and in store, while also providing a merchant's end customers with a vastly improved and modern support experience that eliminates many of the issues customers face today with legacy underwriters. More recently, Extend also launched a shipping protection solution, covering consumers in the case of lost, damaged or stolen packages. This is further expanding the company’s addressable market and value creation for merchants.

We are a venture-backed startup in downtown San Francisco led by founders who have previously had multiple successful exits. Extend simplifies the technology stack for the product and shipping protection industries.

About the Role:

You will be part of the Risk Analytics team building Extend’s fraud detection capabilities and application. You will play a pivotal role in helping to manage risk and scale the organization. 

What You’ll Be Doing:

  • Develop technologies and strategies to prevent and detect claim fraud and abuse across a variety of post-purchase products, including product protection and shipping protection
  • Build and deploy machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
  • Be responsible for evaluating, monitoring, and maintaining models to ensure high performance and reliability
  • Closely partner with product, engineering, and operations teams to productionalize and reduce and prevent fraud 
  • Cultivate a culture of learning and collaboration within and across partner teams

What We’re Looking For: 

  • 3+ years of work experience building and deploying machine learning systems into production
  • Previous experience building fraud detection or risk assessment tools is a strong plus
  • Solid understanding of fundamental computer science concepts, software design best practices, software development lifecycle and common machine learning design patterns
  • Expertise in Python/R, SQL
  • Experience with AWS, dbt
  • Excellent stakeholder management, with a track record of working cross-functionally to deliver results
  • Attention to details and intellectual curiosity to understand user behavior and patterns
  • Empathy and humility

Estimated Pay Range: $150,000 - $170,000 per year salaried*

* The target base salary range for this position is listed above. Individual salaries are determined based on a number of factors including, but not limited to, job-related knowledge, skills and experience.

Life at Extend:

  • Working with a great team from diverse backgrounds in a collaborative and supportive environment.
  • Competitive salary based on experience, with full medical and dental & vision benefits.
  • Stock in an early-stage startup growing quickly.
  • Very generous, flexible paid time off policy.
  • 401(k) with Financial Guidance from Morgan Stanley.

Extend CCPA HR Notice




Top Skills

Python
R
SQL
The Company
San Francisco, CA
181 Employees
On-site Workplace
Year Founded: 2019

What We Do

Extend allows any merchant to offer extended warranties and protection plans through our easy-to-integrate APIs or pre-built eCommerce applications. We power extended warranties both online and offline while also providing consumers with a modern, digitally native experience that eliminates the issues customers face today with legacy offerings.

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