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Staff/Senior Data Scientist, Algorithm (Risk & Fraud)

San Francisco

SpringCube

Full-time - Senior Engineer

Fintech

Posted 4 weeks ago

Disclosed upon interview

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Job Description

The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.

Company Overview

A leading global fintech organization is redefining the future of payments and financial services through a unified platform that supports businesses worldwide. With a strong international presence and a rapidly growing team of technology professionals, the company delivers integrated solutions across payments, business accounts, spend management, treasury, and embedded finance. The organization fosters a culture of innovation, ownership, and collaboration while empowering employees to solve complex challenges at a global scale.

The organization is seeking a Staff/Senior Data Scientist, Algorithm (Risk & Fraud) to join its risk platform team. This role offers the opportunity to work on complex machine learning challenges within the international payments and fraud domain while building industry-leading risk and fraud detection systems.

The successful candidate will design and implement end-to-end machine learning solutions that deliver measurable business impact. They will collaborate with cross-functional teams to develop scalable models, enhance fraud prevention capabilities, and contribute to the evolution of intelligent risk management platforms.

Key Responsibilities

  • Analyze business requirements and translate them into machine learning problems.
  • Develop and implement end-to-end machine learning solutions to address business challenges.
  • Perform data engineering, feature engineering, model training, and deployment activities.
  • Conduct regular analysis to identify issues and propose effective solutions.
  • Build machine learning platforms and tools to improve and streamline ML workflows.
  • Collaborate with cross-functional teams to deploy machine learning models that solve business problems.
  • Contribute to the development of scalable risk management and fraud detection systems.
  • Support innovation in real-time risk assessment and intelligent decision-making processes.

Required Qualifications

  • Minimum of 3+ years of experience working with machine learning libraries such as scikit-learn, TensorFlow, PyTorch, and Keras.
  • Bachelor’s degree or higher in Computer Science, Engineering, or a related technical discipline.
  • Strong programming skills in Python and SQL.
  • Experience in payment risk or international e-commerce risk is considered an advantage.
  • Experience applying Large Language Models (LLMs) to real-time risk management environments is a plus.
  • Strong analytical, problem-solving, and communication skills.
  • Ability to work effectively in a collaborative, fast-paced, and globally distributed environment.

Disclaimer

SpringCube curates tech job listings from various company websites to support tech professionals globally.

  1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
  2. No Client Relationship: This company is not a client of SpringCube unless stated.
  3. To Apply: Click the Apply button to be redirected to the hiring company’s application page for this job.
  4. No Liability: SpringCube is not liable for inaccuracies.

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SpringCube is a specialist career platform for AI, Data & Cloud Engineering professionals, connecting top ML, data, and cloud talent with leading tech employers hiring across the San Francisco Bay Area.

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