Manager, Data Scientist - Recommendation & Personalization Systems

Capital One; New York (NY); On-site; USD 100,000 - 140,000; Full time

Job summary

Capital One is seeking a Data Scientist in New York, NY to partner with teams in delivering products that delight customers. The ideal candidate will have a strong foundation in machine learning with at least 4 years of experience, especially in deep learning and MLOps practices. Proficiency in Python and data processing frameworks like H2O and Spark is essential. The role includes building and maintaining scalable ML systems and requires a Bachelor’s degree or higher in a quantitative field. Comprehensive benefits are offered.

Qualifications

• At least 1 year of experience leveraging open source programming languages for large scale data analysis.
• 3+ years of hands-on experience building, deploying, and maintaining high-scale, production-grade ML systems.
• Deep expertise in developing and optimizing state-of-the-art Deep Learning models.

Responsibilities

• Partner with a cross-functional team to deliver a product customers love.
• Leverage a broad stack of technologies to reveal insights from data.
• Build machine learning models through all phases of development.

Skills

Python

Machine Learning

Data Analysis

AWS

H2O

Spark

PyTorch

DASK

PySpark

Education

Bachelor's Degree in a quantitative field

Master's Degree in a quantitative field

PhD in a quantitative field

Tools

Conda

Kubeflow

CI/CD pipelines

Job description

* 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* 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.* Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.* 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.* 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.* 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:* 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* A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 6 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 4 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) plus 1 year of experience performing data analytics* PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics* 3+ years of hands-on experience building, deploying, and maintaining high-scale, production-grade ML systems using MLOps practices, including AWS, Kubeflow, and CI/CD pipelines* Deep expertise (4+ years) in developing and optimizing state-of-the-art Deep Learning models, specifically Transformer-based architectures, using PyTorch and distributed training with multi-GPU optimization* Extensive experience (4+ years) with high-performance, distributed data processing for petabyte-scale feature engineering using frameworks like DASK and PySparkCapital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.