Lead Data Scientist - Card Finance Forecasting

Capital One

North Dakota

On-site

USD 162,000 - 185,000

Full time

14 days+
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Job summary

Capital One is seeking a Principal Associate, Data Scientist for the Card Finance Innovation Team in the United States. You will work with data scientists, software engineers, and product managers to deliver customer-centric data products using a modern stack (Python, Conda, AWS, Spark, Snowflake).

You’ll build models through all development stages and translate technical work into business outcomes. Ideal candidates have a STEM Master’s (or PhD) and 3+ years in data analytics, ML, and SQL, with

Qualifications

  • Master’s Degree in STEM field plus 3 years of experience in data analytics or a PhD in STEM field
  • At least 3 years of experience in Python, Scala, or R
  • At least 3 years of experience with machine learning
  • At least 3 years of experience with SQL
  • At least 1 year of experience working with AWS

Responsibilities

  • Partner with cross-functional data scientists, software engineers, and product managers to deliver a product customers love
  • Leverage Python, Conda, AWS, H2O, Spark and more to reveal insights in large datasets
  • Build machine learning models through all development phases: design, training, evaluation, validation, implementation
  • Translate complex work into tangible business goals

Skills

Python
Scala
R
Machine learning
SQL
AWS

Education

Master’s Degree in STEM + 3 years experience
PhD in STEM

Tools

Conda
Spark
H2O
Snowflake

Job description

Capital One is seeking a Principal Associate, Data Scientist for the Card Finance Innovation Team in the United States. You will work with data scientists, software engineers, and product managers to deliver customer-centric data products using a modern stack (Python, Conda, AWS, Spark, Snowflake).

You’ll build models through all development stages and translate technical work into business outcomes. Ideal candidates have a STEM Master’s (or PhD) and 3+ years in data analytics, ML, and SQL, with

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