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Lead Data Scientist, Banking

Reposted 5 Hours Ago
Easy Apply
Hybrid
New York, NY
215K-275K
Senior level
Easy Apply
Hybrid
New York, NY
215K-275K
Senior level
Lead the development and governance of machine learning models for risk underwriting, manage a team, and optimize data strategies for consumer credit risk.
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Lead Data Scientist, Banking

Current is a leading consumer fintech platform transforming financial access for everyday Americans with over five million members. We provide access to financial solutions that seamlessly work together to solve the needs of our members and enable all Americans to build better financial futures. Based in NYC, our results-driven environment drives us to build better products, grow faster and empower everyone on our team to have an impact on our business and mission to improve financial outcomes.

We are in search of an experienced Data Scientist to lead our ML model development for our lending and liquidity products. In this role, you will leverage VertexAI to lead the design, development, deployment, and governance of machine learning models that power and optimize our risk underwriting to achieve business objectives. The ideal candidate will possess a strong background in statistical analysis, machine learning techniques, and programming, and preferably a solid understanding of the Credit Risk domain and VertexAI’s capabilities, along with experience in deploying and scaling models using Scala and Google Dataflow.

Responsibilities:

  • Design, develop, and deploy models that are used for risk underwriting, risk management, limit setting, pricing, and customer acquisition and engagement optimization.
  • Analyze diverse datasets, including but not limited to credit bureau, customer behavior, and alternative data, to extract meaningful insights and patterns, identifying actionable opportunities for optimization and innovation.
  • Lead and mentor a team of data scientists and analysts, providing guidance and support.
  • Conduct exploratory data analysis, feature engineering, and model selection to optimize performance and enhance predictive accuracy.
  • Implement and maintain scalable machine learning pipelines and workflows on Google Cloud Platform, ensuring reliability, scalability, and efficiency.
  • Leverage Google Dataflow to process large-scale data and build scalable data processing pipelines.
  • Evaluate model performance and govern deployed models using appropriate metrics, techniques, and scalable automated methods.
  • Maintain model documentation and perform ongoing refits/retraining of existing models to ensure models are always at or near optimal performance and risks of degradation are avoided or managed.
  • Design experiments, measure, test, and conduct readouts to optimize and test the underwriting process, offers, and customer engagement.
  • Collaborate with engineering teams to integrate machine learning models into production systems, monitor performance, and troubleshoot issues.
  • Contribute to developing best practices, standards, and documentation for machine learning processes and methodologies.
  • Develop and implement data-driven strategies for credit risk management.

Requirements:

  • 7+ years of experience in data science or machine learning roles, with expertise in developing and deploying machine learning models, preferably with a background in consumer credit risk and the lending space.
  • 2+ years of experience leading and managing data scientists and/or data analysts.
  • Degree in Computer Science, Statistics, Mathematics, or a related field.
  • Proficiency in Python programming and machine learning libraries (e.g., TensorFlow, scikit-learn) for model development and deployment.
  • Proficiency in data preprocessing, feature engineering, and model selection techniques to optimize performance.
  • Familiarity with Google Cloud Platform services, particularly VertexAI and Dataflow, for scalable data processing and model training.
  • Proficiency in SQL and at least one programming language for developing scalable and efficient machine learning solutions.
  • Understanding of credit risk models and methodologies.
  • Strong leadership, communication, and collaboration skills.
  • Ability to work effectively in a fast-paced, cross-functional environment.
  • Strong understanding of statistical analysis, hypothesis testing, and experiment design.
  • Excellent problem-solving skills with the ability to translate business requirements into technical solutions.

Preferred:

  • Experience using the Scala programming language for developing scalable and efficient machine learning solutions.
  • 2+ years of experience building and deploying models using Vertex AI.
  • Experience in B2C Fintech or Financial Services domain(s).

This role has a base salary range of $215,000- $275,000. Compensation is determined based on experience, skill level, and qualifications, which are assessed during the interview process. Current offers a competitive total rewards package which includes base salary, equity, and comprehensive benefits.

Benefits:

  • Competitive salary
  • Meaningful equity in the form of stock options
  • 401(k) plan
  • Discretionary performance bonus program
  • Biannual performance reviews
  • Medical, Dental and Vision premiums covered at 100% for you and your dependents
  • Flexible time off and paid holidays
  • Generous parental leave policy
  • Commuter benefits
  • Fitness benefits
  • Healthcare and Dependent care FSA benefit
  • Employee Assistance Programs focused on mental health
  • Healthcare advocacy program for all employees
  • Access to mental health apps
  • Team building activities
  • Our modern Chelsea-based office with open floor plan, stocked kitchen, and catered lunches

Top Skills

Google Cloud Platform
Google Dataflow
Python
Scala
Scikit-Learn
SQL
TensorFlow
Vertexai

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