Description
Remote
Our client seeks a Principal Data Scientist to scale Data Science and AI capabilities for end-to-end payment optimization. The role will collaborate with ML engineers and product partners to design and deploy real-time models and intelligent decision engines, drive strategy and roadmaps, lead cross-functional initiatives, and mentor senior data science talent. The position balances strategic leadership with hands-on contribution across architecture, design reviews, code reviews, and select implementation to deliver production-grade ML solutions.
This is a contract to hire opportunity. Applicants must be willing and able to work on a w2 basis and convert to FTE following contract duration. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance.
Responsibilities
- Define technical vision and strategy for data-driven product initiatives focused on payment optimization, aligned to business goals.
- Develop scalable and reusable capabilities for real-time ML models including classification, ranking, optimization, rapid experimentation, and continuous monitoring.
- Oversee and contribute to conceptualization, development, deployment, operation, validation, and maintenance of ML models and update systems.
- Establish and enforce best practices for ML modeling while evaluating and adopting modern tools, frameworks, and infrastructure.
- Foster a culture of innovation, experimentation, and collaboration while mentoring an elite team of data scientists.
- Partner with product, engineering, data, and compliance teams to integrate ML into products and communicate complex concepts to varied audiences.
- Collaborate with Data Science leaders to establish an operating model for ML R&D that optimizes end-to-end delivery of business value.
Experience Requirements
- Bachelor's or master's degree in Computer Science, Statistics, Mathematics, Engineering, or related field. PhD preferred.
- 7+ years in ML research or engineering with 5+ years building large-scale, real-time ML systems in production, including hands-on experience.
- Expertise in machine learning, statistical modeling, and data analysis with strong experience across the ML lifecycle and experimentation.
- Proficiency in Python (Pandas, NumPy, scikit-learn) and strong SQL experience. NoSQL or graph databases are a plus.
- Demonstrated ability to lead solution design and execution, translating complex business requirements into actionable technology solutions.
- Exceptional communication skills with the ability to influence and collaborate across technical and business audiences, including executives.
- Bonus: Experience in payments, fintech, or financial services. Knowledge of payment systems such as authorization lifecycle, tokenization, fraud and risk, and real-time payments. Experience with cloud platforms including AWS, Google Cloud Platform, Snowflake, Databricks, or Vertex AI. Agile development experience. Background in large companies, mature ML teams, or regulated industries.
Education Requirements
- Bachelor's or master's degree in a relevant field. PhD preferred.