Salary
💰 $130,000 - $150,000 per year
About the role
- Combine data sources and apply multiple data and algorithmic approaches to create a clear, cohesive, static and temporal picture of banking customers, actionable for both humans and algorithms.
- Collaborate with business partners to develop meaningful segments to target and optimize consumer interactions based on shared preferences and behaviors.
- Partner with our machine learning engineers to refine and extend our Reinforcement Learning-based marketing optimization capabilities.
- Create well-organized datasets and data processing, algorithm implementations and recommended visualizations that can support implementation in our platform software and documentation, feature and functionality descriptions and customer engagement as needed
- Proactively explore available data to size and project opportunities to improve our products, services or client and consumer experience.
Requirements
- 5+ years experience and a demonstrable track record of delivering applied machine learning or data science capabilities in consumer-facing and/or enterprise applications.
- Independently prototyped, optimized, validated, managed, operated and updated machine learning and statistical models.
- Knowledge of statistical inference, experiment design, probability, sampling methodologies, regression, classification, clustering, data mining, time series analysis, causal inference analysis, neural networks and deep learning techniques.
- Experience in reinforcement learning and multi-armed bandit applications is highly preferred.
- Strong working knowledge of Python-based ML frameworks and cloud computing environments.
- Exceptional communication skills for diverse audiences; strong interpersonal skills and ability to influence.
- Advanced degree (PhD preferred) or equivalent career experience in Computer Science, Applied Mathematics, Statistics or related technical discipline