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Extend

Senior Machine Learning Data Scientist

Posted 21 Days Ago
Remote
Hiring Remotely in US
150K-170K
Mid level
Remote
Hiring Remotely in US
150K-170K
Mid level
Develop and deploy machine learning models to detect fraud and enhance decision-making, collaborating with cross-functional teams on implementation.
The summary above was generated by AI

About Extend:

Extend is revolutionizing the post-purchase experience for retailers and their customers by providing merchants with AI-driven solutions that enhance customer satisfaction and drive revenue growth. Our comprehensive platform offers automated customer service handling, seamless returns/exchange management, end-to-end automated fulfillment, and product protection and shipping protection alongside Extend's best-in-class fraud detection. By integrating leading-edge technology with exceptional customer service, Extend empowers businesses to build trust and loyalty among consumers while reducing costs and increasing profits.


Today, Extend works with more than 1,000 leading merchant partners across industries, including fashion/apparel, cosmetics, furniture, jewelry, consumer electronics, auto parts, sports and fitness, and much more. Extend is backed by some of the most prominent technology investors in the industry, and our headquarters is in downtown San Francisco.

About the Role:

As a Machine Learning Data Scientist on Extend’s Risk & Fraud Machine Learning Team, you will develop and deploy cutting-edge machine learning models to detect and prevent fraud, enhance decision-making, and drive business value. You’ll work closely with product, engineering, and operations teams to build scalable, production-ready machine learning applications that support Extend’s post-purchase products, including product protection, shipping protection, and more. 

What You’ll Be Doing:

  • Develop and deploy machine learning models to prevent and detect fraud and abuse, leveraging structured and unstructured data sources.
  • Own the end-to-end ML lifecycle, including data preprocessing, feature engineering, model training, evaluation, validation, and deployment.
  • Monitor and maintain models in production to ensure performance and reliability over time.
  • Collaborate with product and engineering teams to integrate machine learning models into production applications.
  • Foster a culture of learning, experimentation, and collaboration within and across partner teams.

What We’re Looking For: 

  • 3+ years of experience building and deploying production machine learning models.
  • Previous experience building fraud detection or risk assessment tools is a strong plus.
  • Solid understanding of fundamental machine learning and computer science concepts, software design best practices.
  • Expertise with Python, including common ML/AI libraries such as Scikit-learn, Pytorch, or Tensorflow.
  • Expertise with SQL; experience with dbt or graph databases is a plus.
  • Familiarity with large language models (LLMs) and their applications in risk and fraud detection.
  • Experience with AWS, cloud computing, and/or Typescript is a plus.
  • Excellent communication and stakeholder management skills, with a track record of working cross-functionally to drive business impact.
  • Attention to detail, intellectual curiosity, and a deep understanding of user behavior and fraud 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.
  • Generous, flexible paid time off policy.
  • 401(k) with Financial Guidance from Morgan Stanley.

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Top Skills

AWS
Cloud Computing
Dbt
Graph Databases
Python
PyTorch
Scikit-Learn
SQL
TensorFlow
Typescript

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