VSA Data Science Intern

  • Foster City, CA, USA
  • Intern

Company Description

Common Purpose, Uncommon Opportunity. Everyone at Visa works with one goal in mind – making sure that Visa is the best way to pay and be paid, for everyone everywhere. This is our global vision and the common purpose that unites the entire Visa team. As a global payments technology company, tech is at the heart of what we do: Our VisaNet network processes over 13,000 transactions per second for people and businesses around the world, enabling them to use digital currency instead of cash and checks. We are also global advocates for financial inclusion, working with partners around the world to help those who lack access to financial services join the global economy. Visa’s sponsorships, including the Olympics and FIFA™ World Cup, celebrate teamwork, diversity, and excellence throughout the world. If you have a passion to make a difference in the lives of people around the world, Visa offers an uncommon opportunity to build a strong, thriving career. Visa is fueled by our team of talented employees who continuously raise the bar on delivering the convenience and security of digital currency to people all over the world. Join our team and find out how Visa is everywhere you want to be.

“Visa will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of Article 49 of the San Francisco Police Code.”

Job Description

nformation security is an integral part of Visa’s
corporate culture.  It is essential to
maintaining our position as an industry leader in electronic payments, and it
is the responsibility of each and every employee to safeguard information,
protect it from unauthorized access, and ensure regulatory compliance.  Information security has a significant effect
on privacy, consumer confidence, external reputation, and/or the bottom line,
and it is a priority on everyone’s agenda.

The successful
candidate will part of Visa Security Analytics program and design, develop and
implement statistical and machine learning anomaly detection models in the Hadoop
ecosystem. Visa Security Analytics (VSA) program has an enterprise security
focus, and is responsive to evolving threat landscape, regulatory compliance,
IT security requirements and technology architecture. The VSA program is part
of cyber security organization, handles long-term retention for security system
logs and security sensor logs.



Responsibilities:

VSA Data Science Intern:

Will be a part of the Security Analytics group and will
primarily focused on entire data science life cycle activities.

  • Cyber security use case requirement gathering, perform
    large-scale data analysis and develop effective statistical and machine
    learning models for improving Cybersecurity capabilities at VISA.

  • Work closely with Data Engineering team to proactively deploy
    data science models and making models operational.

  • Responsible for all the data scientist model development
    life  – analysis, design, build, test,
    deploy and operationalization.

  • Suggest improvements in the tools and techniques to help
    scale the team always look out for continuous improvement from technology and
    process perspective

  • The successful candidate should be adoptive to the
    Visa's agile environment

Qualifications

irements/Qualifications:



  • MS or PhD degree in a quantitative discipline (applied
    mathematics, statistics, computer science, operations research, or related
    field) from a leading academic institution

  • Expert knowledge of an analysis tool such as R,SAS or
    Matlab

  • Comfortable on the command line and with Unix core tools

  • Strong Programmer - Python, Perl, Java, and/or C++.
    Experience with relational database (SQL, PL*SQL) is a plus

  • Experience working with distributed computing tools a
    plus (Hadoop, PIG, etc.)

  • Thorough knowledge of supervised and unsupervised
    modeling techniques.

  • Comfort analyzing large, complex, high-dimensional
    datasets

  • Strong passion for empirical research and answering hard
    questions with data

  • Demonstrated success presenting complex research data
    (qualitative and quantitative) in a clear and compelling manner that inspires
    action

  • Experience utilizing both qualitative analysis (e.g.,
    content analysis, phenomenology, hypothesis testing) and quantitative analysis
    techniques (e.g., clustering, regression, pattern recognition, descriptive and
    inferential statistics)


Additional Information

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