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Director, Data Science Machine Learning Engineer - Enterprise Model Risk

Employer
Capital One
Location
McLean, Virginia
Closing date
Jul 24, 2022

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Job Details

Center 2 (19050), United States of America, McLean, Virginia

Director, Data Science Machine Learning Engineer - Enterprise Model Risk

Director - Data Scientist

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.

Team Description

In Capital One's Model Risk Office, we defend the company against model failures and find new ways of making better decisions with models. We use our statistics, software engineering, and business expertise to drive the best outcomes in both Risk Management and the Enterprise. We understand that we can't prepare for tomorrow by focusing on today, so we invest in the future: investing in new skills, building better tools, and maintaining a network of trusted partners. We learn from past mistakes, and develop increasingly powerful techniques to avoid their repetition. As a Director of Data Science in the Model Risk Office, on any given day you'll be:
  • Identifying, assessing and quantifying the risks stemming from open source software dependencies, as well as the design of effective strategies and controls for managing the risks of the model software supply chain. You will also be a thought partner to leaders of the Center for Machine Learning and Delivery Experience for the Software Delivery Life Cycle at Capital One (SDLC), helping them design and build software supply chains that effectively manage model risk
  • Identifying, assessing, and quantifying the risks stemming from data service interactions and service orchestration platforms. You will also be a thought partner to the leaders of the Center for Machine Learning and other Technology teams building our next generation of Feature Computation and Machine Learning Platforms, helping them design and build platforms that effectively manage model risk
  • Assessing, challenging, and at times defending state-of-the-art decision-making systems to internal and regulatory partners
  • Distilling disparate details of complex interconnected systems into concrete actions with clear value
  • Overseeing development of benchmark and challenger models to stress test critical modeling decisions
  • Developing new ways of identifying weak spots in model predictions earlier and with more confidence than the best available methods
  • Constructing software tools that make models better


Role Description

In this role, you will:
  • Partner with a cross-functional team of data scientists, software engineers, and product managers to manage the risk and uncertainty inherent in statistical models in order to lead Capital One to the best decisions, not just avoid the worst ones.
  • Leverage a broad stack of technologies - Python, R, Conda, AWS, Spark, and more - to reveal the insights hidden within huge volumes of numeric and textual data
  • Build and validate machine learning models through all phases of development, from design through training, evaluation, and implementation
  • Flex your interpersonal skills to translate the complexity of your work into tangible business goals, and challenge model developers to advance their modeling, data, and analytic capabilities


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.
  • A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond.
  • 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. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.



A successful Candidate will have:
  • Experience setting and implementing broad strategic vision for ML applications, underlying platforms, and software
  • Demonstrated technical open source community involvement through software contributions, posters, presentations, and other participation. Expertise in testing of machine learning and statistical software. Experience with open source software packaging, environment management, and reproducibility
  • Demonstrated experience with compute orchestration tools such as AirFlow, Prefect, Nomad, Kubernetes, and ECS. Expertise in model service paradigms, model interface languages such as JSON and protobuf, and testing strategies for machine learning and statistical software


Basic Qualifications:
  • Bachelor's Degree plus 9 years of experience in data analytics, or Master's Degree plus 7 years of experience in data analytics, or PhD plus 4 years of experience in data analytics
  • At least 4 years of experience in open source programming languages for large scale data analysis
  • At least 4 years of experience with machine learning
  • At least 4 years of experience with relational databases


Preferred Qualifications:
  • PhD in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 5 years of experience in data analytics
  • At least 1 year of experience working with AWS
  • At least 3 years of experience managing people
  • At least 5 years of experience in Python, Scala, or R for large scale data analysis
  • At least 5 years of experience with machine learning


Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

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, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

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 RecruitingAccommodation@capitalone.com . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Company

We Don’t Only Think Big Things—At Capital One, We Do Big Things.

You’re dedicated to your career. You deserve professional satisfaction and personal fulfillment. You belong at Capital One.

Here, every day brings another chance to do impactful work that matters: helping millions of customers confidently manage their money, building stronger communities and delivering truly disruptive tech. You’ll give your all alongside some of the brightest, most resilient people in the industry—and in return, you’ll enjoy the growth opportunities, support, flexibility and benefits you need for an exhilarating life both on and off the job.

Be inspired. Be yourself. That’s #LifeAtCapitalOne.

Creating a Culture of Belonging

At Capital One, we value diversity, inclusion and belonging at our core. We’re building a place of belonging—where everyone can feel seen, heard, valued and free to be their authentic selves. We want to be a place of opportunity—where associates from all backgrounds innovate for our customers and communities, and build meaningful, fulfilling careers.

We endeavor to be a welcoming and inspiring place for all. We seek and embrace diversity. And we’re committed to having a diverse and inclusive workforce, focused on increasing the representation of underrepresented groups, strengthening our culture of inclusion and belonging and harnessing our scale to invest in our communities.

We’re focused on three core principles to advance diversity, inclusion and belonging across Capital One:

Create a culture of belonging where everyone can thrive and innovate

Attract and develop talent from all backgrounds and experiences

Ensure our systems and programs promote fairness and equity

Get a career with more at Capital One.  Discover it for yourself today.

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, race, color, age, national origin, religion, sexual orientation, gender identity, protected veteran status, disability or other protected status.

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