Manager, Data Scientist – Capital One Data Insights and Analytics

Capital One; New York (NY); On-site; USD 120,000 - 160,000; Full time

Job summary

Capital One in New York seeks a data analytics professional to partner across teams, building ML models and validating insights with robust statistical methods. You will modernize data infrastructure using open-source tools and cloud platforms, while delivering real-time validation controls and supporting complex banking projects.

The role emphasizes experience in data science, ML, and SQL, with preferred background in banking data and AWS familiarity.

Qualifications

• Bachelor's degree in a quantitative field required.
• Master's or MBA with quantitative concentration or PhD pathway.
• Experience with open-source languages for large-scale data analysis.
• Experience with machine learning.
• Experience with relational databases.
• Hands-on data science solution development using open-source tools and cloud platforms.
• Experience building, validating, and backtesting models.
• Experience with clustering, classification, time series, sentiment analysis, and deep learning.

Responsibilities

• Partner with cross-functional data scientists, business analysts, and relationship managers to deliver client value.
• Partner with enterprise AI teams to build ML models from design through implementation.
• Conduct statistical analysis and back-testing against third-party data to validate insights.
• Modernize data infrastructure by developing analytical tools on core enterprise data schemas.
• Implement real-time automated validation controls.
• Support technical integrations for run-off analysis, underwriting automation, and risk/portfolio management.
• Research and evaluate emerging technologies and identify opportunities to apply state-of-the-art methods.

Skills

Data Analytics

Machine Learning

Statistical Analysis

Python/Scala/R

SQL

Time Series

Deep Learning

Embeddings

AWS

Clustering

Education

Bachelor's Degree in Quantitative Field

Master's Degree in Quantitative Field or MBA

PhD in Quantitative Field

PhD in STEM plus 3 years experience (preferred)

Tools

Relational Databases

Cloud Computing Platforms

AWS

Job description

Partner with cross-functional data scientists, business analysts, and relationship managers to deliver client value
Partner with enterprise AI teams to build machine learning models through design, training, evaluation, validation, and implementation
Conduct statistical analysis and back-testing against third-party data to integrate datasets and validate insights
Modernize data infrastructure by developing analytical tools on core enterprise data schemas
Implement real-time automated validation controls
Support technical integrations for complex business projects, including run-off analysis, underwriting automation, and advanced risk and portfolio management
Research and evaluate emerging technologies and identify opportunities to apply state-of-the-art methods

Requirements

• Currently has, or is in the process of obtaining, a required degree by the scheduled start date
• Bachelor's Degree in a quantitative field plus 6 years of experience performing data analytics; or Master's Degree in a quantitative field or MBA with a quantitative concentration plus 4 years; or PhD in a quantitative field plus 1 year
• At least 1 year of experience leveraging open source programming languages for large scale data analysis
• At least 1 year of experience working with machine learning
• At least 1 year of experience utilizing relational databases
• Hands-on experience developing data science solutions using open-source tools and cloud computing platforms
• Experience building, validating, and backtesting models
• Experience with clustering, classification, sentiment analysis, time series, and deep learning
• Skills retrieving, combining, and analyzing data from varied sources and structures
• PhD in STEM plus 3 years of experience in data analytics (preferred)
• At least 1 year of experience working with AWS (preferred)
• At least 4 years' experience in Python, Scala, or R for large scale data analysis (preferred)
• At least 4 years' experience with machine learning and embeddings (preferred)
• At least 4 years' experience with SQL (preferred)
• Experience working with consumer and/or commercial banking data (preferred)
• Capital One will consider sponsoring a new qualified applicant for employment authorization

Core Competencies

Demonstrates expertise in data analytics, machine learning, and statistical analysis, with a strong focus on developing and validating models using open-source programming languages and cloud computing platforms. Proficient in leveraging relational databases and modernizing data infrastructure to deliver actionable insights and client value.

Highest-signal resume keywords

• Data Analytics
• Machine Learning
• Statistical Analysis
• Python, Scala, or R
• SQL

Hard Skills

• Data Analysis
• Machine Learning
• Statistical Analysis
• Model Validation
• Back-Testing
• Clustering
• Classification
• Sentiment AnalysisTime Series
• Deep Learning

Certifications & Qualifications

• Bachelor's Degree in Quantitative Field
• Master's Degree in Quantitative Field or MBA
• PhD in Quantitative Field

Industry Keywords

• Consumer Banking Data
• Commercial Banking Data
• Data Infrastructure
• Analytical Tools
• Automated Validation Controls

Tools & Technologies

• Open Source Programming Languages
• Cloud Computing Platforms
• Relational Databases
• AWS