Principal Associate, Data Scientist - Cash Flow...

Capital One Financial Corporation
Chicago, IL, United States
2 days ago

Role details

Contract type
Permanent contract
Employment type
Part-time / full-time
Experience required
1 year minimum
Compensation
$161,800.0 - $184,600.0
Working hours
Regular working hours
Job source

Tech stack

Amazon Web Services Data Analysis Big Data Python (Programming Language) Machine Learning Open Source Technology Sentiment Analysis SQL Databases Transaction Data Cloud Platform System Apache Spark Deep Learning
+2 more
Information Technology Data Analytics

Job description

We are looking for highly analytical Data Scientists to join our Cash Flow Underwriting Team. This role is centered on leveraging advanced machine learning techniques to identify and engineer the predictive signals that power our risk and usage models.

The ideal candidate possesses a solid understanding of data alongside advanced machine learning skills to uncover non-obvious patterns in cash flow and transaction data. You will be responsible for applying sophisticated methodology to transform raw banking data into high-value features that accurately forecast creditworthiness and customer behavior.

Role Description

In this role, you will:

  • 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 the insights hidden within huge volumes of numeric and textual data

  • Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation

  • Flex your interpersonal skills to translate the complexity of your work into tangible business goals

Requirements

  • Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers.

  • Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea.

  • Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.

  • Statistically-minded. You’ve 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, and deep learning.

  • A data guru. “Big data” doesn’t faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science.

Basic Qualifications:

  • Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:

  • A Bachelor’s Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 5 years of experience performing data analytics

  • A Master’s Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 3 years of experience performing data analytics

  • A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field)

Preferred Qualifications:

  • Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)

  • At least 1 year of experience working with AWS

  • At least 3 years’ experience in Python, Scala, or R

  • At least 3 years’ experience with machine learning

  • At least 3 years’ experience with SQL

Benefits & conditions

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.

Cambridge, MA: $161,800 - $184,600 for Princ Associate, Data Science

Chicago, IL: $147,100 - $167,900 for Princ Associate, Data Science

About the company

Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making., Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website (https://www.capitalonecareers.com/benefits) . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level., Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.juju.com

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

2:34 min

Capabilities of the Apache Spark processing engine

Ayon Roy ¡ LIVE

3:28 min

Defining big data and machine learning fundamentals

Ayon Roy ¡ LIVE

1:48 min

Automating exploratory data analysis within training pipelines

Dora Petrella ¡ WWC 2023

3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou ¡ Coffee With Developers

2:10 min

Why organizations combine big data and machine learning

Ayon Roy ¡ LIVE

3:09 min

Balancing data science skillings alongside systems engineering rigor

Nico Schmidt ¡ LIVE

Videos

See all

Related articles

See all