Lead Data Scientist - Personalization & Recommendations

Information Technology Senior Management Forum; McLean (VA); On-site; USD 162,000 - 185,000; Full time

Benefits offered by this job

Sponsorship available

Health benefits

Performance-based incentives

Job summary

Capital One is seeking a Principal Associate, Data Scientist to advance personalized recommendations and experimentation across our data-rich platforms. You will collaborate with cross-functional teams to deploy scalable ML models handling billions of interactions.

You’ll work with Python, Spark, AWS and cutting-edge techniques to translate complex data into business impact, present findings to partners, and help shape the next generation of customer experiences.

Qualifications

• Bachelor's degree in a quantitative field plus 5 years of data analytics experience.
• Master’s degree in a quantitative field (Statistics, Economics, OR Analytics, Mathematics, CS) or MBA with a quantitative concentration plus 3 years of data analytics experience.
• PhD in a quantitative field (Statistics, Economics, OR Analytics, Mathematics, CS)

Responsibilities

• Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love.
• Leverage a broad stack of technologies – Python, Conda, AWS, H2O, Spark, and more – to reveal insights from large data sets.
• Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation.
• Translate the complexity of your work into tangible business goals for stakeholders

Skills

Python

Scala

R

SQL

AWS

Education

Bachelor's degree in a quantitative field

Master’s degree in a quantitative field or MBA with quantitative concentration

PhD in a quantitative field

Tools

Python

Spark

Conda

AWS

Job description

Capital One is seeking a Principal Associate, Data Scientist to advance personalized recommendations and experimentation across our data-rich platforms. You will collaborate with cross-functional teams to deploy scalable ML models handling billions of interactions.

You’ll work with Python, Spark, AWS and cutting-edge techniques to translate complex data into business impact, present findings to partners, and help shape the next generation of customer experiences.