Director, Data Science - Model Risk Office at Capital One (Washington DC)
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.
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
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
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
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.
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