11 Sep
Principal Associate, Data Science
Virginia, Richmond 00000 Richmond USA

Vacancy expired!

Recruiting : NY - New York, United States of America, New York, New York

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 on a mission to help 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.

Principal Associate, Data Science

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 100 company and a leader in the world of data-driven decision-making.

As a Data Scientist on Capital One’s People Analytics team, you’ll be on the leading edge of applying analytics to talent, combining machine learning and social science to build strategies that expand Capital One’s talent advantage.

Team Description

The People Analytics Center of Excellence at Capital One is a 75 person cross-functional team of analysts, consultants, and data scientists.

The People Analytics Talent Assessment & Analytics team builds models that help Capital One assess and select great talent.

We partner with vendors to implement world class assessment solutions for the business, as well as develop our own. We derive insights, build models and develop strategies using Python, AWS, and other open-source technology.

We deliver analytics to internal customers in intelligent and real time custom web applications.

Role Description

In this role, you will :

Build models and perform analyses centered on helping Capital One assess and select great talent.

These could include :

Building custom models to assess quality of hire for a given function or more broadly, all in service of developing better candidate assessment solutions

Optimizing each aspect of our recruiting operation from assessing, selecting and hiring candidates to sourcing & engaging them.

Supporting our efforts to deploy assessment technologies using best in class fairness methods.

Leverage a broad stack of technologies Python, AWS, GitHub RedShift, and more to reveal the insights hidden within huge volumes of recruiting data

Build predictive models through all phases of development, from design through training, evaluation, validation, and implementation

Writing white papers that explain predictive models you have developed

Flex your interpersonal skills to translate the complexity of your work into tangible business outcomes

The Ideal Candidate is

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.

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.

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, NLP and deep learning.

Basic Qualifications :

Bachelor’s Degree plus 5 years of experience in data analytics, or Master’s Degree plus 3 years in data analytics, or PhD

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 1 year experience with NLP

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

Vacancy expired!


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