Manager, Data Science

Capital One Financial

Confirmed live today Low trust

Quick summary

Work type
On-site
Location
McLean, VA
Employment
Full-time
Posted
49 days ago
Freshness
Confirmed live today
Nearby
99+ roles within 25 mi

Market check

Salary context

How this pay compares to similar roles

Similar $190k
$133k $235k
below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $164,512–$214,500.

Based on 240 similar postings.

Employer

About Capital One Financial

Capital One Financial is a bank holding company specializing in credit cards, auto loans, banking, and savings products, known for its data-driven approach to consumer and commercial finance. Industry: Financial Services & Banking

Capital One Financial currently has 2107 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1107 roles with salary data.

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At a glance

TL;DR · Manager, Data Science

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The Manager, Data Science joins the Card DS team to innovate how the business handles data through analytics, infrastructure, and strategy. In this role, you will partner with a cross-functional team of data scientists, software engineers, and product managers to build and maintain solutions that drive smart business decisions. You will develop machine learning models through all phases of development, including design, training, evaluation, validation, and implementation. To solve complex business problems using petabytes of numeric and textual data, you will leverage a broad stack including Python, Conda, AWS, H2O, Spark, PyTorch, and DASK. Key technical competencies include clustering, classification, sentiment analysis, time series analysis, and deep learning to extract relevant insights from large-scale data and cloud-based processing environments.

What does a Data Science Manager earn?

Median $211200 from 43 postings across 13 companies.

See salary data

Skills

Python AWS Spark PySpark H2O Conda PyTorch Kubeflow DASK CI/CD MLOps Relational Databases Deep Learning Transformer Statistical Modeling Time Series Analysis Sentiment Analysis Clustering Classification

What you'll do

  • Build machine learning models through all phases of development including design, training, evaluation, and implementation.
  • Leverage a broad technology stack including Python, AWS, H2O, and Spark to extract insights from large datasets.
  • Develop data science solutions from initial concept to production using open source tools and cloud platforms.
  • Perform feature engineering and data processing for petabyte-scale numeric and textual data.
  • Translate complex technical work into tangible business goals for non-technical audiences.
  • Partner with cross-functional teams of engineers and product managers to deliver customer-facing products.
  • Validate and backtest models using statistical metrics like confusion matrices and ROC curves.

What we're looking for

  • Must have a Bachelor's in a quantitative field plus 6 years of data analytics experience, a Master's/MBA plus 4 years, or a PhD plus 1 year.
  • Must have at least 1 year of experience leveraging open source programming languages for large scale data analysis.
  • Must have at least 1 year of experience working with machine learning.
  • Must have at least 1 year of experience utilizing relational databases.
  • Must have hands-on experience developing data science solutions from concept to production using open source tools and modern cloud platforms.
  • Must have experience with clustering, classification, sentiment analysis, time series analysis, and deep learning.
  • PhD in a STEM field plus 3 years of experience in data analytics (preferred).
  • 3+ years of experience building and maintaining production-grade ML systems using MLOps, AWS, Kubeflow, and CI/CD (preferred).

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