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Staff Data Scientist, Fraud

Posted 2024-11-17

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💎 Seniority level: Staff, 7+ years

💸 Salary: 190000 - 260000 USD per year

🔍 Industry: Home services marketplace

🗣️ Languages: English

⏳ Experience: 7+ years

Requirements:
  • Master’s or Ph.D. in a quantitative field such as Computer Science, Statistics, or Mathematics.
  • 7+ years of experience in data science and machine learning, focusing on fraud detection.
  • Expertise in machine learning and deep learning models, including working knowledge of large language models.
  • Familiarity with advanced algorithms like Graph NN, Reinforcement Learning, and unsupervised learning for fraud detection.
  • Proven track record of deploying impactful machine learning models.
  • Proficiency in SQL and Python, with experience in cloud ML solutions.
  • Excellent communication skills for conveying technical concepts to non-technical stakeholders.
Responsibilities:
  • Lead development of state-of-the-art machine learning models and algorithms to improve fraud detection.
  • Implement highly optimized models for seamless deployment and scalability in production.
  • Collaborate with engineers, data scientists, and product managers on machine learning systems.
  • Foster innovation by exploring new approaches to solve complex business problems.
  • Mentor junior team members and promote a culture of continuous learning.
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💸 190000 - 260000 USD per year

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  • Master’s or Ph.D. in a quantitative field (e.g., Computer Science, Statistics, Mathematics).
  • 7+ years of experience in data science & machine learning, focusing on real-time models and fraud.
  • Expertise in machine learning and deep learning, particularly with large language models.
  • Knowledge of algorithms like Graph NN, Reinforcement Learning, and unsupervised learning approaches.
  • Proven track record in deploying impactful machine learning models.
  • Proficient in SQL and Python, experience with cloud ML solutions.
  • Excellent communication skills for conveying technical concepts.

  • Lead development of machine learning models to improve fraud detection.
  • Implement optimized models for scalable deployment.
  • Collaborate with engineers, data scientists, and product managers on machine learning systems.
  • Foster innovation within the team to solve complex problems.
  • Mentor junior team members and encourage knowledge sharing.
Posted 2024-11-17
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  • Master's or Ph.D. in a quantitative field (e.g., Computer Science, Statistics, Mathematics).
  • 7+ years of experience in data science & machine learning, focusing on real-time models within tech or marketplaces.
  • Expertise in machine learning and deep learning; knowledge of large language models.
  • Proficiency in state-of-the-art algorithms for fraud detection.
  • Proficiency in SQL and Python; experience with cloud ML solutions.
  • Excellent communication skills to convey complex concepts to non-technical stakeholders.

  • Lead development of machine learning models and algorithms for fraud detection.
  • Implement optimized models for seamless deployment and scalability.
  • Collaborate with engineers, data scientists, product managers, and designers.
  • Foster innovation in solving complex business problems.
  • Guide junior team members and promote a culture of learning.
Posted 2024-11-17
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🧭 Full-Time

💸 190000 - 260000 USD per year

🔍 Home services / Online marketplace

  • Master's or Ph.D. in a quantitative field (e.g., Computer Science, Statistics, Mathematics).
  • 7+ years of experience in data science & machine learning, specifically focused on real-time ML models and fraud.
  • Expertise in machine learning, deep learning, and large language models.
  • Experience with algorithms such as Graph NN, Reinforcement Learning, and unsupervised learning for fraud detection.
  • Proven track record of deploying impactful machine learning models into production.
  • Proficiency in SQL and Python, with experience in cloud ML solutions.
  • Excellent communication skills to convey complex technical concepts to non-technical stakeholders.

  • Lead development of machine learning models to improve fraud detection across the marketplace.
  • Implement highly optimized models for seamless deployment and scalability in production.
  • Collaborate with engineers, data scientists, product managers, and designers on end-to-end development.
  • Encourage innovation within the team and explore new techniques to solve business problems.
  • Mentor junior team members and promote continuous learning and technical excellence.
Posted 2024-11-17
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