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Data Science Manager - Python Standards Implementation

Employer
Capital One
Location
McLean, Virginia
Closing date
Jun 19, 2021

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Job Details

1750 Tysons (12023), United States of America, McLean, Virginia

Data Science Manager - Python Standards Implementation

At Capital One, we're building a leading information-based technology company. Still founder-led by Chairman and Chief Executive Officer Richard Fairbank, Capital One is focused on helping our customers succeed by bringing ingenuity, simplicity, and humanity to banking. We measure our efforts by the success our customers enjoy and the advocacy they exhibit. We are succeeding because they are succeeding.

Guided by our shared values, we thrive in an environment where collaboration and openness are valued. We believe that innovation is powered by perspective and that teamwork and respect for each other lead to superior results. We elevate each other and obsess about doing the right thing. Our associates serve with humility and a deep respect for their responsibility in helping our customers achieve their goals and realize their dreams. Together, we are on a quest to change banking for good.

As a Manager Data Scientist in the Retail and Direct Bank, you'll be part of a high performing team that is working to define the next generation of banking. The Bank Data Science team has a relentless focus on the craft of modeling, coding, and innovation with a target towards continually improving customer experience and delivering value to the business. Using the latest in machine learning and distributed computing technologies, you will be building the next generation of data products to enable automation and aim for the right decision at the right time for in-the-moment action.

T his role is centered around the application of Python and its flexibility across imperative, object-oriented, and functional programming styles. It includes building reusable assets in a Pythonic environment and embodies core principles of The Zen of Python. While an early focus of the role will be on designing and building the model development and execution patterns of the future, there will remain a consistent and ultimately primary intent to establish, educate, and evangelize the best practices required of data scientists to successfully use these platforms with robust and resilient code. The role requires a willingness to teach these principles to other members on the team.

In this role you will:
  • Own in-house developed tools & libraries in support of statistical and machine learning model building and deployment to various execution platforms including:
    • New tool and platform discovery and investigation
    • Technical documentation in support of playbook(s) standards, FAQs
    • Tool adoption, modification, and development to standardize, automate and inner-source best practices for data source access, model development, model promotion to production and model monitoring
  • Leverage expertise on platforms and software best practices to enable and improve data scientists' code resiliency and performance including:
    • Developing or curating training for software development best practices for data scientist mastery on model build and execution platforms
    • Developing code and repo quality standards and train data scientists to adopt and adhere to these standards with structured peer code reviews
    • Host office hours or other avenues to assist data scientists in need of assistance on model build and execution platforms and tools
    • Engage with the data science community to solicit feedback and lead virtual or in-person training sessions
    • Develop and maintain up to date playbooks for the tools and development practices


Basic Qualifications
  • Bachelor's Degree plus 6 years of experience in data analytics, or Master's Degree plus 4 years in data analytics, or PhD plus 1 year of experience in data analytics
  • At least 2 years of experience in open source programming languages for large scale data analysis
  • At least 2 years of experience with machine learning
  • At least 2 years of experience with relational databases


Preferred Qualifications:
  • Bachelor's Degree or Master's Degree in Computer Science, Computer Engineering, Statistics, Math plus 3 years of experience in data analytics
  • At least 1 year of experience and proficiency in working with AWS (S3, EMR, EC2, IAM, Lambda)
  • At least 2 years of experience with containerization (Docker)
  • At least 4 years of experience working in Python
  • At least 4 years of experience with PyData software stacks (pandas, numpy, scipy, sklearn, statsmodels)
  • At least 4 years of experience with machine learning
  • At least 4 years of experience with SQL


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

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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