Data Science Lead for Card Upmarket Acquisitions

Jobtailor; Massachusetts; On-site; USD 120,000 - 180,000; Full time

Job summary

Capital One is seeking a data scientist to partner with data scientists, engineers, and product managers to deliver customer-focused analytics products. You will build ML models using Python, AWS, Spark, and related open-source tools to analyze large volumes of numeric and textual data.

You will own model lifecycles from design to deployment, monitoring, and governance, translating complex data science work into clear business outcomes and partnering with cross-functional teams to drive impact.

Qualifications

• Bachelor's degree in a quantitative field plus 6 years of experience performing data analytics
• Master's/MBA with quantitative concentration plus 4 years of experience
• PhD plus 1 year of experience in quantitative field

Responsibilities

• Partner with data scientists, software engineers, and product managers to deliver customer-focused products
• Use Python, Conda, AWS, H2O, Spark, and related technologies to analyze large volumes of numeric and textual data
• Build machine learning models through design, training, evaluation, validation, and implementation
• Translate complex data science work into tangible business goals
• Own model lifecycles including development, deployment, monitoring, governance, usage expansion, and releases
• Collaborate with data engineers, platform engineers, product managers, credit analysts, and business analysts
• Lead talent development and challenge conventional thinking to improve solutions

Skills

Machine Learning Model Development

Python Programming

AWS Cloud Computing

Data Analysis with Open-Source Tools

Relational Database Utilization

Education

Bachelor's degree in a quantitative field

Master's degree or MBA with quantitative concentration

PhD in a quantitative field

Tools

Conda

H2O

Spark

Job description

Capital One is seeking a data scientist to partner with data scientists, engineers, and product managers to deliver customer-focused analytics products. You will build ML models using Python, AWS, Spark, and related open-source tools to analyze large volumes of numeric and textual data.

You will own model lifecycles from design to deployment, monitoring, and governance, translating complex data science work into clear business outcomes and partnering with cross-functional teams to drive impact.