Capital One National Association
Senior Associate, Data Scientist - Servicing Intelligence
Capital One National Association, Mc Lean, Virginia, us, 22107
Center 1 (19052), United States of America, McLean, VirginiaSenior Associate, Data Scientist - Servicing Intelligence
Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.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.Team Description:
The Servicing Intelligence data science team builds models to help our internal customers use unstructured, multi-modal data sources — text, image, and audio data. We partner with product, engineering, and business teams to deliver solutions spanning from using generative AI to conduct information extraction on millions of documents to analyzing call transcripts to identify customer pain points. You will be the driving force to experiment, innovate, and create next generation experiences powered by the latest emerging generative AI technologies.Role Description:
In this role, you will:Leverage Natural Language Processing (NLP), Computer Vision, Speech, large language models (LLMs), large multi-modal models (LMMs) and traditional modeling approaches like GBMs for advanced customer servicing applications.
Utilize a broad stack of technologies like Python, Pytorch, HuggingFace, LangChain, Spark, Kubernetes, Docker, AWS Cloud, Github etc., for model development and deployment.
Analyze and derive insights from both structured and unstructured data sources.
Collaborate on a team of data scientists and engineers to build machine learning models through all phases of development, from design through training, evaluation, validation, implementation, and maintenance.
Flex your communication skills by interacting with a variety of internal business stakeholders to define innovative data science solutions.
Grasp underlying business processes, getting into the details by guiding annotators to curate high quality, consistent training datasets.
The Ideal Candidate is:
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.
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.
Statistically-minded. You’ve built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve.
Basic Qualifications:
Currently has, or is in the process of obtaining a Bachelor’s Degree plus 3 years of experience in data analytics, or currently has, or is in the process of obtaining Master’s Degree plus 1 year of experience in data analytics 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:
At least 2 years of experience in Python with a blend of experiences in data science and software engineering.
At least 2 years of experience with machine learning.
At least 1 year of experience working with unstructured data for natural language processing, computer vision, or speech applications.
At least 1 year of experience fine-tuning and deploying transformer based models.
At least 1 year of experience working with deep learning libraries and tools, such as Pytorch and HuggingFace.
At least 1 year of experience working with AWS.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.New York City (Hybrid On-Site): $138,500 - $158,100 for Sr Assoc, Data Science.Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.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.Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the
Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.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. Capital One promotes a drug-free workplace.
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Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.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.Team Description:
The Servicing Intelligence data science team builds models to help our internal customers use unstructured, multi-modal data sources — text, image, and audio data. We partner with product, engineering, and business teams to deliver solutions spanning from using generative AI to conduct information extraction on millions of documents to analyzing call transcripts to identify customer pain points. You will be the driving force to experiment, innovate, and create next generation experiences powered by the latest emerging generative AI technologies.Role Description:
In this role, you will:Leverage Natural Language Processing (NLP), Computer Vision, Speech, large language models (LLMs), large multi-modal models (LMMs) and traditional modeling approaches like GBMs for advanced customer servicing applications.
Utilize a broad stack of technologies like Python, Pytorch, HuggingFace, LangChain, Spark, Kubernetes, Docker, AWS Cloud, Github etc., for model development and deployment.
Analyze and derive insights from both structured and unstructured data sources.
Collaborate on a team of data scientists and engineers to build machine learning models through all phases of development, from design through training, evaluation, validation, implementation, and maintenance.
Flex your communication skills by interacting with a variety of internal business stakeholders to define innovative data science solutions.
Grasp underlying business processes, getting into the details by guiding annotators to curate high quality, consistent training datasets.
The Ideal Candidate is:
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.
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.
Statistically-minded. You’ve built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve.
Basic Qualifications:
Currently has, or is in the process of obtaining a Bachelor’s Degree plus 3 years of experience in data analytics, or currently has, or is in the process of obtaining Master’s Degree plus 1 year of experience in data analytics 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:
At least 2 years of experience in Python with a blend of experiences in data science and software engineering.
At least 2 years of experience with machine learning.
At least 1 year of experience working with unstructured data for natural language processing, computer vision, or speech applications.
At least 1 year of experience fine-tuning and deploying transformer based models.
At least 1 year of experience working with deep learning libraries and tools, such as Pytorch and HuggingFace.
At least 1 year of experience working with AWS.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.New York City (Hybrid On-Site): $138,500 - $158,100 for Sr Assoc, Data Science.Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.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.Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the
Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.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. Capital One promotes a drug-free workplace.
#J-18808-Ljbffr