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Locations: VA - McLean, United States of America, McLean, VirginiaSenior Associate Data ScientistSr Assoc, Data Science , Anti-Money Laundering Modeling and Advanced Data InsightsData 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'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 the big opportunities that help everyday people save money, time and agony in their financial lives.Team DescriptionThe Anti-Money Laundering (AML) Modeling and Advanced Data Insights team is on a journey to modernize the way Capital One identifies potential money laundering, fraud, terrorist financing, and human trafficking through the use of advanced analytic techniques, statistics, and machine learning models. We develop predictive models, monitoring dashboards, and reporting using tools such as AWS, Snowflake, Python, and Spark. Our team produces the model outputs and data insights to operate our AML program efficiently and effectively. As the model developer for advancing transaction monitoring with machine learning, our team is responsible for end to end development, deployment, and monitoring of production models.Role DescriptionIn this role, you will:• Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love• Leverage a broad stack of technologies - Python, Conda, AWS, Spark, and more - to reveal the insights hidden within huge volumes of numeric and textual data• Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation• Flex your interpersonal skills to translate the complexity of your work into tangible business goalsThe 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, and deep learning.• A data guru. "Big data" doesn't faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science.Basic Qualifications:• Currently has, or is in the process of obtaining a Bachelor's Degree plus 3 years of experience in data analytics, or currently has, or is in the process of obtaining Master's Degree plus 1 year of experience in data analytics with an expectation that required degree will be obtained on or before the scheduled start date• 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 databasesPreferred Qualifications:• Master's Degree in "STEM" field (Science, Technology, Engineering, or Mathematics), or PhD in "STEM" field (Science, Technology, Engineering, or Mathematics)• Experience working with AWS• At least 2 years' experience in Python, Scala, or R• At least 2 years' experience with machine learning• At least 2 years' experience with SQL• Experience with Anti-Money Laundering and developing models in a regulated environmentCapital One will consider sponsoring a new qualified applicant for employment authorization for this position.Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.This role is expected to accept applications for a minimum of 5 business days.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 (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable 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.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 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.comCapital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.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).
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What You Should Know About Senior Associate Data Scientist, Capital One

Are you ready to dive deep into the world of data as a Senior Associate Data Scientist at Capital One in Richmond, VA? You’ll find yourself at the heart of a dynamic team that’s transforming how we tackle issues like money laundering and fraud detection. Forget traditional methods! You'll leverage advanced analytics, big data, and machine learning techniques to craft predictive models that not only identify financial irregularities but also drive real change in the financial lives of our customers. Your toolkit will include the latest technologies like AWS, Python, and Spark, allowing you to analyze massive datasets while working collaboratively with software engineers and product managers. The ideal candidate is not only technically proficient but also brings innovative ideas to the table and enjoys tackling complex, undefined problems. If you're passionate about statistics and have a knack for building models that apply to real-world scenarios, we want to hear from you! Jump into this exciting opportunity and help us advance our Anti-Money Laundering initiatives while working in a culture that values creativity, growth, and excellence.

Frequently Asked Questions (FAQs) for Senior Associate Data Scientist Role at Capital One
What are the primary responsibilities of a Senior Associate Data Scientist at Capital One?

As a Senior Associate Data Scientist at Capital One, your main responsibilities will include developing predictive models for Anti-Money Laundering efforts, utilizing advanced analytics and machine learning techniques. You'll collaborate with cross-functional teams, leveraging tools like Python and AWS to extract actionable insights from large volumes of data, ensure the end-to-end deployment of analytics solutions, and communicate findings effectively to meet business goals.

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What qualifications do I need to apply for the Senior Associate Data Scientist position at Capital One?

To qualify for the Senior Associate Data Scientist role at Capital One, you should have a Bachelor's degree plus three years of experience in data analytics or a Master's degree with a year of experience. Proficiency in open-source programming, machine learning, and relational databases is essential. Preferred qualifications include a Master's or PhD in a STEM field, familiarity with AWS, and significant experience using Python or similar languages.

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How does Capital One support career development for Senior Associate Data Scientists?

Capital One is committed to fostering a culture of continuous learning and development. As a Senior Associate Data Scientist, you will have access to a variety of training programs, mentorship opportunities, and resources to stay current with emerging technologies and methodologies in the field, ensuring that you are always equipped to tackle new challenges and advance your career.

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What technologies do Senior Associate Data Scientists work with at Capital One?

Senior Associate Data Scientists at Capital One work with an exciting stack of technologies including Python, AWS, Spark, and various data visualization and machine learning tools. This modern tech stack enables you to build and deploy advanced analytics solutions that have a significant impact on the company's anti-money laundering efforts.

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Is prior experience in Anti-Money Laundering required for the Senior Associate Data Scientist role at Capital One?

While prior experience in Anti-Money Laundering is preferred, it is not strictly required for the Senior Associate Data Scientist position at Capital One. Candidates with a strong analytics background, machine learning know-how, and an eagerness to learn about the regulatory aspects of AML are strongly encouraged to apply.

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Common Interview Questions for Senior Associate Data Scientist
Can you describe your experience with machine learning techniques?

To effectively answer this question, provide specific examples of machine learning projects you've worked on, discussing the algorithms or models you used, the data you analyzed, and the outcomes of your efforts. Highlight your ability to evaluate model performance and make iterative improvements based on results.

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How do you approach a dataset that contains missing values?

When addressing missing values, explain your methodology clearly. Discuss techniques such as imputation, removal, or utilizing algorithms capable of handling missing data, and describe instances where you've successfully applied these methods to maintain data integrity while ensuring insightful analysis.

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What tools do you use for data visualization in your projects?

Be prepared to discuss the visualization tools you're familiar with, such as Matplotlib, Seaborn, or Tableau. Give examples from your past work that show how you effectively communicated complex data insights to non-technical stakeholders through visual formats.

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Describe a successful project where you collaborated with a cross-functional team.

Here, you should share a specific example detailing the project, your role, and how you collaborated with team members from different disciplines. Emphasize how cooperation enriched the project outcome and how you contributed to aligning goals across the team.

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What challenges have you faced while deploying machine learning models into production?

Discuss any challenges such as data quality issues, the need for model retraining, or integration with existing systems. Explain how you addressed these challenges and what strategies you implemented to ensure a smooth deployment process.

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How do you stay current with advancements in data science and analytics?

To tackle this question, share your strategies for learning about new technologies or methodologies, such as attending conferences, participating in online courses, or engaging with industry-related communities. Highlight an example of how you applied a new technique in your work.

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What experience do you have with cloud platforms, particularly AWS?

Describe your experience with AWS in your data projects, mentioning specific services used (e.g., S3, EC2, SageMaker). Highlight any projects where AWS tools boosted the efficiency or scalability of your machine learning applications.

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Can you explain a complex data science concept to a non-technical audience?

Choose a complex concept you've worked with and practice explaining it simply. Focus on using everyday analogies that relate to the audience's experience, ensuring your explanation is engaging and comprehensible without technical jargon.

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What is your experience with statistical analysis, and how have you applied it in your projects?

Detail your experience with statistical analysis techniques and tools, discussing how you applied these methods to derive insights from data in your projects. Provide examples that demonstrate your ability to interpret results and apply them to decision-making processes.

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Why are you interested in working at Capital One?

Reflect on your research about Capital One's mission and values. Explain how your personal goals align with their focus on innovation, data-driven solutions, and customer-centric approaches, ideally tying these values back to your passion for data science and impactful work.

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All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran

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Full-time, on-site
DATE POSTED
December 9, 2024

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