Principal Associate, Data Science - enterprise Model Risk

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

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! Fastforward 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 datadriven decisionmaking.

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 big opportunities that help everyday people save money, time and agony in their financial lives.

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 also 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.

Role Description

In this role, you will:

• Dive into all types of models to see what makes them tick, where they might break, and how to make them better every model is different and brings a new challenge

• Leverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, R and more — to reveal insights hidden within huge volumes data

• Build upon your existing machine learning toolset both by learning new technologies and by building custom tools for data exploration, model performance evaluation, and more

• Flex your interpersonal skills to translate the complexity of your work into tangible actions that directly impact our customers

The Ideal Candidate is:

• 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.

• You’re comfortable with opensource languages and are passionate about developing further. You have handson experience developing data science solutions using opensource tools and cloud computing platforms.

• Statisticallyminded. 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.

• You continually research and evaluate emerging technologies. You stay current on published stateoftheart methods, technologies, and applications and seek out opportunities to apply them.

Basic Qualifications:

• At least a PhD OR a Master’s Degree and a minimum of 1 year experience OR a Bachelor’s Degree and a minimum of 6 years of experience
• At least 1 year experience in open source programming languages for large scale data analysis
• At least 1 year experience with machine learning
• At least 1 year experience with relational databases
• At least 1 year experience with SQL

Preferred Qualifications:

• 3+ years’ experience in open source programming languages for large scale data analysis
• 3+ years’ experience with machine learning
• 3+ years’ experience with relational databases
• 3+ years’ experience with SQL