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Team Description
As part of Consumer ML, you will:
Explore billions of clickstream events to discover the patterns in customer behavior, and use those patterns to model key customer outcomes
Develop the real-time models that use vast amounts of customer data to anticipate customers’ needs and deliver the right options at the right time
Develop the models that ensure our most important customer data is accurate, fighting fraud and other bad behavior, while enabling seamless digital experiences across all our products
Role Description
In Consumer Identity ML, you will work at all phases of the data science life cycle, including:
improve operationalizationin scalable and resilient production systems that serve 50+ million customers.
Partner closely with a variety of business and product teams across Capital One to conduct the experiments that guide improvements to customer experiences and business outcomes in domains like marketing, servicing and fraud prevention.
Write software (Python, e.g.) to collect, explore, visualize and analyze numerical and textual data (billions of customer transactions, clicks, payments, etc.) using tools like Spark.
The Ideal Candidate is
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.
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 back tested 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 a Bachelor’s Degree plus 5 years of experience in data analytics, or currently has, or is in the process of obtaining a Master’s Degree plus 3 years in data analytics, or currently has, or is in the process of obtaining PhD, with an expectation that required degree will be obtained on or before the scheduled start date
At least 1 year of experience in open source programming languages for large scale data analysis
At least 1 year of experience with machine learning
At least 1 year of experience with relational databases
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)
Specialized experience in the fields of Information Retrieval, NLP, Data-centric AI, and Knowledge Graphs
At least 3 years’ experience in PyTorch/Tensorflow
At least 3 years’ experience with machine learning
At least 1 year of experience working with AWS
New York City (Hybrid On-Site): $165,100 - $188,500 for Data Science PhD
San Francisco, California (Hybrid On-site): $174,900 - $199,700 for Data Science PhD
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
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