Capital One
Principal Associate, Data Scientist - Transaction Intelligence
Capital One, New York, New York, us, 10261
Data is at the center of everything we do. This role is for a Data Scientist on Capital One's Transaction Intelligence team, leveraging transaction data to power at-scale, real-time experiences for customers. The team uses Python, Spark, Snowflake, Databricks and Kubeflow to build models and tools that serve customers and the analytics community at Capital One.
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, Spark, Databricks, Snowflake, and more — to reveal insights hidden within large volumes of numeric and textual data Build machine learning models through all phases of development: design, training, evaluation, validation, and implementation Translate complex technical work into tangible business goals Explore and apply the latest advances in machine learning, including transformer modeling architectures, to real-world problems in financial services The Ideal Candidate
Innovative: able to apply the latest ML developments to real-world financial services problems Technical: comfortable with a broad technology stack Creative: experienced in building and deploying end-to-end ML models A data guru: adept at retrieving, combining, and analyzing data from diverse sources and structures Basic Qualifications
Currently have, or are in the process of obtaining, one of the following degrees with the expectation it will be completed by the start date: A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or related) plus 5 years of data analytics experience A Master's Degree in a quantitative field (or MBA with quantitative concentration) plus 3 years of data analytics experience A PhD in a quantitative field Preferred Qualifications
Master’s Degree in STEM plus 3 years of data analytics experience, or PhD in STEM At least 1 year of experience with AWS 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 Compensation and Benefits : Capital One will sponsor eligible applicants. The minimum and maximum full-time annual salaries are location-dependent. This role may be eligible for performance-based incentives, which could include cash bonuses and/or long-term incentives. Capital One offers a comprehensive benefits package. Eligibility varies by status and role. Additional Information : Capital One is an equal opportunity employer (EOE, including disability and veteran status). Capital One maintains a drug-free workplace and complies with applicable laws regarding criminal background inquiries. For accommodations in the application process, contact Recruiting at 1-800-304-9102 or RecruitingAccommodation@capitalone.com. For recruiting process questions, please email Careers@capitalone.com. Capital One does not endorse third-party products or services found on external sites. Note: This role is based in New York, NY or other eligible locations as posted. This description reflects the responsibilities and requirements of the role as of the date issued and may be subject to change.
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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, Spark, Databricks, Snowflake, and more — to reveal insights hidden within large volumes of numeric and textual data Build machine learning models through all phases of development: design, training, evaluation, validation, and implementation Translate complex technical work into tangible business goals Explore and apply the latest advances in machine learning, including transformer modeling architectures, to real-world problems in financial services The Ideal Candidate
Innovative: able to apply the latest ML developments to real-world financial services problems Technical: comfortable with a broad technology stack Creative: experienced in building and deploying end-to-end ML models A data guru: adept at retrieving, combining, and analyzing data from diverse sources and structures Basic Qualifications
Currently have, or are in the process of obtaining, one of the following degrees with the expectation it will be completed by the start date: A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or related) plus 5 years of data analytics experience A Master's Degree in a quantitative field (or MBA with quantitative concentration) plus 3 years of data analytics experience A PhD in a quantitative field Preferred Qualifications
Master’s Degree in STEM plus 3 years of data analytics experience, or PhD in STEM At least 1 year of experience with AWS 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 Compensation and Benefits : Capital One will sponsor eligible applicants. The minimum and maximum full-time annual salaries are location-dependent. This role may be eligible for performance-based incentives, which could include cash bonuses and/or long-term incentives. Capital One offers a comprehensive benefits package. Eligibility varies by status and role. Additional Information : Capital One is an equal opportunity employer (EOE, including disability and veteran status). Capital One maintains a drug-free workplace and complies with applicable laws regarding criminal background inquiries. For accommodations in the application process, contact Recruiting at 1-800-304-9102 or RecruitingAccommodation@capitalone.com. For recruiting process questions, please email Careers@capitalone.com. Capital One does not endorse third-party products or services found on external sites. Note: This role is based in New York, NY or other eligible locations as posted. This description reflects the responsibilities and requirements of the role as of the date issued and may be subject to change.
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