Principal Data Scientist - Emerging ML

Description

This is an individual contributor position. In Emerging ML, you will work at all phases of the data science lifecycle, including :

Build machine learning models through all phases of development, from design through training, evaluation and validation, and partner with engineering teams to operationalize them in scalable and resilient production systems that serve 50+ million customers.

Partner closely with a variety of business and product teams across Capital One to conduct the experiments that guide improvements to customer experiences and business outcomes in domains like marketing, servicing and fraud prevention.

Write software (Python, Scala, e.g.) to collect, explore, visualize and analyze numerical and textual data (billions of customer transactions, clicks, payments, etc.

using tools like Spark and AWS.

The Ideal candidate will be :

Curious and creative. You thrive on bringing definition to big, undefined problems. You love asking questions, and you love pushing hard to find the answers.

You’re not afraid to share a new idea. You communicate clearly and effectively to share your findings with non-technical audiences.

Technical : You have hands-on experience developing data science solutions from concept to production using open source tools and modern cloud computing platforms.

You are not afraid of petabytes of data.

Statistically-minded. You have built models, validated them and backtested them. You know how to interpret a confusion matrix or a ROC curve.

You have experience with clustering, classification, sentiment analysis, time series analysis and deep learning.

Customer and product oriented. You share our passion for changing banking for good.

Basic Qualifications

Currently has, or is in the process of obtaining a Bachelor’s Degree plus 5 years of experience in data analytics, or currently has, or is in the process of obtaining a Master’s Degree plus 3 years in data analytics, or currently has, or is in the process of obtaining PhD, with an expectation that required degree will be obtained on or before the scheduled start date

At least 1 year of experience in open source programming languages for large scale data analysis

At least 1 year of experience with machine learning

At least 1 year of experience with relational databases

Preferred Qualifications :

Masters in STEM field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics

Experience building transformer models at scale (>

100M parameters)

Understanding of self-supervised learning methods

Strong foundation in software engineering

At least 1 year of experience working with AWS

At least 2 years’ experience in Python, Scala, or R for large scale data analysis

At least 2 years' experience with machine learning

At least 2 years' experience with SQL

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting.

Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

New York City (Hybrid On-Site) : $165,100 - $188,500 for Data Science PhD

San Francisco, California (Hybrid On-site) : $174,900 - $199,700 for Data Science PhD