What are the responsibilities and job description for the Principal Data Scientist, Marketing Intelligence position at Karkidi?
As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
Take the next step in your career now, scroll down to read the full role description and make your application.The Marketing Data Science team, within the Card organization, is working to enable a revolution in marketing through the use of data science and machine learning. The vast amount of data, variety of quickly-evolving marketing channels, and hunger for analytics all intersect to make Capital One's marketing space a target-rich environment for optimization through data science and machine learning. We use a full spectrum of data science and machine learning techniques to solve unique marketing challenges, and our growing team is just scratching the surface of what we can do.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, 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.The Ideal candidate will be : Curious and creative. You thrive on bringing definition to big, undefined problems. You love asking questions, and you love pushing hard to find the answers. You’re not afraid to share a new idea. You communicate clearly and effectively to share your findings with non-technical audiences.Technical : You have hands-on experience developing data science solutions from concept to production using open source tools and modern cloud computing platforms. You are not afraid of petabytes of data.Statistically-minded. You have built models, validated them and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series analysis and deep learning.Customer and product oriented. You share our passion for changing banking for good.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).At least 1 year of experience working with AWS.At least 3 years’ experience in Python, Scala, or R.At least 3 years’ experience with machine learning.At least 3 years’ experience with SQL.Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law.
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