Amount-posted 4 months ago
$165,000 - $192,500/Yr
101-250 employees

We are seeking a talented and strategic Data Scientist to join our team and take ownership of our model development, selection, and optimization, with a focus on fraud and risk. In this critical role, you will be responsible for overseeing, maintaining, and evolving our current in-house models using machine learning techniques. You will also play a key part in shaping our long-term fraud and risk strategy, including evaluating and potentially integrating third-party models to complement our homegrown offerings. The ideal candidate is a strong data scientist who has applied those skills to fraud and risk decisioning in finance. They possess a proven ability to translate complex data into actionable business insights and effectively communicate with internal and external stakeholders. This role will have a strong product bias, but will also have a significant client-facing component in working with our customers to maximize their product performance.

  • Oversee the entire lifecycle of our proprietary models, including monitoring their performance, identifying areas for improvement, and implementing enhancements with advanced machine learning algorithms.
  • Lead the evolution of our core fraud prevention capabilities via our fraud models, including improving in-house capabilities and assessing third-party fraud models.
  • Ensure that all models are governed appropriately and serve as a subject matter expert when interacting with customers regarding models.
  • Work closely with our Policy Optimizer product, leveraging statistical methods to help clients configure their credit policies and improve key performance indicators.
  • Help customers maximize their lending and onboarding product portfolios by evolving and maximizing their credit and fraud policies.
  • Partner with Product, Engineering, and Customer Success teams to ensure our models are effectively integrated and delivering maximum value.
  • Proactively analyze large datasets to uncover trends, identify new risks, and discover opportunities for product innovation and performance improvement.
  • 7+ years of professional experience in a data science role, with a strong emphasis on credit and/or fraud risk management within the financial services or fintech industry.
  • Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, or related field.
  • Proficiency in Python and SQL for data manipulation, modeling, and analysis.
  • Hands-on experience developing, validating, and implementing machine learning models (e.g., Logistic Regression, Gradient Boosting, Random Forest, Neural Networks).
  • Familiarity with decision tree analysis and its application in a business context.
  • A deep understanding of statistical concepts and the ability to apply them to solve complex business problems.
  • Excellent verbal and written communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences.
  • A strategic thinker who is comfortable with ambiguity and can navigate complex challenges independently.
  • Experience working with large-scale datasets and cloud-based data platforms (e.g., AWS, GCP, Azure).
  • Familiarity with model validation best practices and regulatory requirements in the financial industry.
  • Previous experience in a client-facing or consulting role.
  • Annual performance bonuses as part of our commitment to shared success.
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