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Manager Data Science Job Opening In McLean – Now Hiring Capital One


Job description

Overview

Manager Data Science

Manager Data Scientist,Representation Learning for Customer Protection

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’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 Description-

The Retail Bank Customer Protection Data Science team has a relentless focus on innovation with a passion for improving customer experiences around fraud prevention.

Detecting and preventing fraud behaviors as early as possible helps keep customer funds secure and enables the Bank to grow with confidence.

Our team is constantly investing to improve and complement existing model-based defenses with the latest and greatest techniques from industry and academia.

We often design features using SQL, python, and spark, and train models using a variety of python-centric modeling libraries.

Data scientists often lead the deployment of these models in batch and event-based environments, and may additionally partner with engineering teams for deployments that interface with other real-time systems.

The team is focused on giving our millions of customers comfort to know that their account is protected from attempts to take it over.

Role Description-

In this role, you will:

  • Leverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, Kubernetes, and more to build sequence models to detect fraud risk using deep learning techniques like transformers, LSTMs, and embeddings of tabular data

  • Connect your deep technical modeling expertise to the pressing business goals of our fraud prevention strategy partners to create exciting solutions to demanding challenges

  • Provide the engine to a research agenda with business opportunities at its heart

  • Partner with a cross-functional team of data scientists, software engineers, business analysts, and product managers to deliver industry leading fraud defenses.

  • Pilot machine learning models through all phases of development, from design through training, evaluation, validation, and implementation

  • The Ideal Candidate is:

  • 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.

  • 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.

  • A leader.

    You challenge conventional thinking and work with stakeholders to identify and improve the status quo.

    You’re passionate about talent development for your own team and beyond.

  • Basic Qualifications:

  • Currently has, or is in the process of obtaining a Bachelor’s Degree plus 6 years of experience in data analytics, or currently has, or is in the process of obtaining a Master’s Degree plus 4 years of experience in data analytics, or currently has, or is in the process of obtaining PhD 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 2 years’ experience in open source programming languages for large scale data analysis

  • At least 2 years’ experience with machine learning

  • At least 2 years’ experience with relational databases

  • Preferred Qualifications:

  • PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics

  • At least 1 year of experience working with AWS

  • At least 4 years’ experience in Python for large scale data analysis

  • At least 4 years’ experience with machine learning and specifically deep learning sequence modeling architectures

  • At least 4 years’ experience with SQL

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

    The minimum and maximum full-time annual salaries for this role are listed below, by location.

    Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting.

    Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

    McLean, VA: $193,400 - $220,700 for Mgr, Data ScienceRichmond, VA: $175,800 - $200,700 for Mgr, Data Science

    Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

    This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI).

    Incentives could be discretionary or non discretionary depending on the plan.

    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.

    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.

    Required Skill Profession

    Mathematical Science Occupations


    • Job Details

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    Unlock Your Manager Data Potential: Insight & Career Growth Guide


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    The Work Culture

    An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at Capital One adheres to the cultural norms as outlined by Expertini.

    The fundamental ethical values are:

    1. Independence

    2. Loyalty

    3. Impartiapty

    4. Integrity

    5. Accountabipty

    6. Respect for human rights

    7. Obeying United States laws and regulations

    What Is the Average Salary Range for Manager Data Science Positions?

    The average salary range for a varies, but the pay scale is rated "Standard" in McLean. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.

    What Are the Key Qualifications for Manager Data Science?

    Key qualifications for Manager Data Science typically include Mathematical Science Occupations and a list of qualifications and expertise as mentioned in the job specification. The generic skills are mostly outlined by the . Be sure to check the specific job listing for detailed requirements and qualifications.

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    Interview Tips for Manager Data Science Job Success

    Capital One interview tips for Manager Data Science

    Here are some tips to help you prepare for and ace your Manager Data Science job interview:

    Before the Interview:

    Research: Learn about the Capital One's mission, values, products, and the specific job requirements and get further information about

    Other Openings

    Practice: Prepare answers to common interview questions and rehearse using the STAR method (Situation, Task, Action, Result) to showcase your skills and experiences.

    Dress Professionally: Choose attire appropriate for the company culture.

    Prepare Questions: Show your interest by having thoughtful questions for the interviewer.

    Plan Your Commute: Allow ample time to arrive on time and avoid feeling rushed.

    During the Interview:

    Be Punctual: Arrive on time to demonstrate professionalism and respect.

    Make a Great First Impression: Greet the interviewer with a handshake, smile, and eye contact.

    Confidence and Enthusiasm: Project a positive attitude and show your genuine interest in the opportunity.

    Answer Thoughtfully: Listen carefully, take a moment to formulate clear and concise responses. Highlight relevant skills and experiences using the STAR method.

    Ask Prepared Questions: Demonstrate curiosity and engagement with the role and company.

    Follow Up: Send a thank-you email to the interviewer within 24 hours.

    Additional Tips:

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    Be Honest: Don't exaggerate your skills or experience.

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    Body Language: Maintain good posture, avoid fidgeting, and make eye contact.

    Turn Off Phone: Avoid distractions during the interview.

    Final Thought:

    To prepare for your Manager Data Science interview at Capital One, research the company, understand the job requirements, and practice common interview questions.

    Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the Capital One's products or services and be prepared to discuss how you can contribute to their success.

    By following these tips, you can increase your chances of making a positive impression and landing the job!

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