Director of Fraud, Risk, and Data Science

A DAY IN THE LIFE:

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.

Reporting: Reports to Chief Product & Technology Officer

Salary: $165,000 - $192,500

Bonus: Amount employees are eligible for annual performance bonuses as part of our commitment to shared success!

Benefits & Perks: Check them out HERE!

WHAT WE’LL TRUST YOU TO DELIVER: 

• Model Development, Management & Evolution: Oversee the entire lifecycle of our proprietary models, including monitoring their performance, identifying areas for improvement, and implementing enhancements with advanced machine learning algorithms.
• Fraud Prevention: Lead the evolution of our core fraud prevention capabilities via our fraud models. This includes improving in-house capabilities, conducting build vs. buy analyses, and assessing third-party fraud models to determine the optimal path forward for Amount and its clients.
• Model Governance: Ensure that all models are governed appropriately and serve as a subject matter expert when interacting with our customers regarding models. You will be responsible for responding to model validation requests, explaining model functionality, and providing evidence of model performance and compliance.
• Policy Optimizer Analysis: Work closely with our Policy Optimizer product, leveraging statistical methods to help clients configure their credit policies, optimize underwriting rules, and improve key performance indicators.
• Customer Success:  Our customers ultimately want to maximize their lending and onboarding product portfolios and this role will help them evolve and maximize their credit and fraud policies to do so.  Via regular meetings, valuable insights will be gained that can be used to inform future product value propositions and feature enhancements.
• Cross-Functional Collaboration: Partner with Product, Engineering, and Customer Success teams to ensure our models are effectively integrated, performing as expected, and delivering maximum value to our clients.
• Data-Driven Insights: Proactively analyze large datasets to uncover trends, identify new risks, and discover opportunities for product innovation and performance improvement.

WHAT YOU LIKELY BRING TO THE TABLE:

• Experience: 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.
• Technical Skills:
  • 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.
• Analytical Mindset: A deep understanding of statistical concepts and the ability to apply them to solve complex business problems. You are skilled at translating data-driven insights into clear, actionable recommendations.
• Communication Skills: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences, including clients and internal stakeholders.
• Problem Solver: You are a strategic thinker who is comfortable with ambiguity and can navigate complex challenges independently.

NICE TO HAVES:

• 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.