Principal Data Scientist

At Capital One 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.

As a Data Scientist at Capital One you will be part of a team thats 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 the big opportunities that help everyday people save money time and agony in their financial lives.

At Capital One India we are at the cutting edge of solving some of the fundamental business problems using advanced data methodologies statistics and machine learning algorithms.

Team Description

The DataLabs Anti-Money Laundering (AML) team is on a journey to modernize the way Capital One identifies potential money laundering terrorist financing and human trafficking using advanced analytic techniques statistics and machine learning models. Our team develops data sourcing predictive models monitoring and reporting using tools such as AWS Snowflake Python and Spark. As the model development team for advancing transaction monitoring with machine learning our team is responsible for end-to-end development deployment and monitoring of these critical risk management models.

Our mission is to empower data-driven decision-making foster innovation without limits and make Capital Ones AML program pre-eminent. We achieve this by implementing rigorous data governance practices constructing analytical data stores and harnessing the power of analytics to unlock valuable insights.

About the Role

• Partner cross-functionally with teams throughout the enterprise including Product and Tech to enable capturing risky behavior. You will enhance your technical and analytical skills while also working with leaders to influence business strategies.
• Collaborate with Quants Data Scientists Data analysts Business analysts and risk managers to drive innovation shape strategic initiatives and propel AML Transaction monitoring to new heights in the data management landscape.
• Utilize data to drive real-world impact and thrive in a collaborative forward-thinking environment
• Assess challenge and sometimes defend state-of-the-art decision-making systems to internal and regulatory partners.
• Build upon your existing machine learning and statistical toolset - both by learning new technologies and by building custom software tools for data exploration model performance evaluation and more.
• Use Open Source/Digital technologies to mine complex voluminous and different varieties of data sources and platforms.
• Build data products data solutions tools and capabilities to enable self-service frameworks for data consumers.
• Demonstrate ability to explore and quickly grasp new technologies to progress varied initiatives.
• Drive analysis that provides meaningful insights on business strategies.
• Communicate technical subject matter clearly and concisely to individuals from various backgrounds both verbally and through written communication; prepare presentations of complex technical concepts and research results to non-specialist audiences and senior management.
• Flex your interpersonal skills to defend the model with validators auditors and regulators.

The ideal candidate is:

• Inquisitive. You thrive on bringing definition to big undefined problems. You love asking questions and pushing hard to find answers. Youre not afraid to share a new idea.
• Technical. Youre 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.
• ML/Statistically minded. Youve built models validated them and back tested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering classification time series and deep learning.
• 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.

Basic Qualifications:

• Bachelors degree in statistics math engineering economics econometrics financial engineering finance or operations research with a quantitative focus.
• At least 4 years relevant work experience in data analytics.
• At least 3 years of experience in Python or R.

Preferred Skills:

• Proficiency in key econometric and statistical techniques (such as predictive modeling logistic regression panel data models decision trees machine learning methods)
• 4 years of experience model development or validation
• 4 years of experience in R or Python for large scale data analysis
• 4 years of experience with relational databases and SQL
• Strong analytical skills with high attention to detail and accuracy
• Excellent written and verbal communication skills
• Experience in financial services industry
• Experience in Fraud / Anti-money Laundering domain

At this time Capital One will not sponsor a new applicant for employment authorization for this position.

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- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

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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).