Lead Data Scientist, Optimization & Decision Systems

Capital One Group; New York, McLean (NY, VA); Presencial; USD 215.000 - 246.000; Tempo integral

Benefícios oferecidos por esta vaga

Incentives based on performance

Resumo da vaga

Capital One is seeking a Manager, Data Scientist - Optimization to lead development of advanced optimization and machine learning solutions across large-scale data infrastructures. You will collaborate with Product, Engineering, and Business teams to translate complex challenges into scalable models and data-driven decisions.

You will guide experiments, validate assumptions, and deploy models that improve decision-making and customer outcomes while leveraging open-source tools and cloud

Qualificações

• Bachelor’s Degree plus 6 years of experience in data analytics or Master’s Degree plus 4 years of experience or PhD plus 1 year of experience in data analytics.
• At least 2 years’ experience in open source programming languages for large scale data analysis
• At least 2 years’ experience with machine learning
• At least 2 years’ experience with relational databases

Responsabilidades

• Design in-market experiments with Product Managers and Business Analysts.
• Formulate and solve complex problems using optimization models (linear, mixed-integer, non-linear, heuristic).
• Build, test, and deploy production-grade optimization algorithms and simulation models using Python and solvers.
• Collaborate with Product, Engineering, and Business teams to integrate optimization engines.
• Build machine learning models through all phases from design to implementation.

Conhecimentos

Machine learning

Relational databases

Open source programming

Python

AWS

Time-series modeling

Formação

Bachelor’s degree

Master’s degree

PhD

Ferramentas

AWS

Python

R

Descrição da vaga

Capital One is seeking a Manager, Data Scientist - Optimization to lead development of advanced optimization and machine learning solutions across large-scale data infrastructures. You will collaborate with Product, Engineering, and Business teams to translate complex challenges into scalable models and data-driven decisions.

You will guide experiments, validate assumptions, and deploy models that improve decision-making and customer outcomes while leveraging open-source tools and cloud