Remote Data Science Manager | ML & Big Data Leader

Capital One; Deerfield (IL); Remote; USD 179,000 - 246,000; Full time

Job summary

Capital One is seeking a Data Science Manager to support Consumer and Developer Experience (CDX) leaders within a dynamic product strategy team. You will collaborate with software engineers, analysts, and product managers to deliver data-driven features across Capital One apps, marketing, and risk analytics against billions of records.

You will design and deploy ML models, translate insights into business value, and lead open-source and cloud-based data science initiatives.

Qualifications

• Bachelor's degree in a quantitative field plus 6 years of analytics
• Master's degree in a quantitative field or MBA with quantitative concentration plus 4 years of analytics
• PhD in a quantitative field plus 1 year of analytics
• At least 1 year of experience leveraging open source languages for large-scale data analysis
• At least 1 year of experience working with machine learning
• At least 1 year of experience utilizing relational databases

Responsibilities

• Partner with cross-functional teams to deliver products customers love that move the needle for the business
• Leverage a broad stack of technologies to reveal insights in massive datasets
• Build machine learning models through all phases from design to implementation
• Translate complex work into tangible business goals

Skills

Python

AWS

Spark

SQL

Machine Learning

Open-source tools

Education

Bachelor's degree (quantitative)

Master's degree or MBA (quantitative)

PhD in quantitative field

Tools

Conda

H2O

Spark

Job description

Capital One is seeking a Data Science Manager to support Consumer and Developer Experience (CDX) leaders within a dynamic product strategy team. You will collaborate with software engineers, analysts, and product managers to deliver data-driven features across Capital One apps, marketing, and risk analytics against billions of records.

You will design and deploy ML models, translate insights into business value, and lead open-source and cloud-based data science initiatives.