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Data Scientist, FeatureSpaceVisa • Austin, Texas, United States
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Data Scientist, FeatureSpace

Visa
  • US
    Austin, Texas, United States
  • US
    Austin, Texas, United States
Apply Now

About

About Us Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid. At Visa, you'll have the opportunity to create impact at scale - tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters - to you, to your community, and to the world. Progress starts with you. Job Description At FeatureSpace, we strive to be the world's best software company at protecting our clients and their customers from fraud attacks. We do that with personality, heart and professionalism, cultivating an innovative, fun and positive team atmosphere where everybody can contribute to solving our clients' problems in new, innovative ways. We are always seeking to be the best at what we do and make our customers smile. The Role In your role as Data Scientist within the Professional Services organization, you will help us achieve our goals and deliver success on behalf of our customers by:
Building advanced statistical models and algorithms that infer and predict individual customer behaviors in real-time, based on retail, online and ecommerce transaction data. This is a customer-facing role that requires close collaboration with clients to understand their data and challenge
Responsibilities:
We hire people with a willingness to adapt to a variable role, so along with the key responsibilities below, we ask for ownership of any other duties as required. Applying analytical theory to diverse real-world problems on large and dynamic datasets Generating integral work products from project kickoff through to live deployment Developing statistical models and algorithms for integration within FeatureSpace products End-to-end processing and modelling of large customer data sets Producing materials to feedback analytic output to customers (reports, presentations, visualizations) Working collaboratively with customers to understand the opportunities and constraints of their existing data in the context of machine learning and predictive modelling Evaluating and improving analytical results on live systems Developing an understanding of industry data structures and processes Working with engineering/development teams to support and enhance the analytical infrastructure Testing analytical models and their integration within the ARIC platform Providing input into future data science strategy and product development Building advanced statistical models and algorithms that infer and predict individual customer behaviors in real-time, based on retail, online and ecommerce transaction data.
We value how we go about our work, just as much as what we do, and this is reflected in our values. As a Data Scientist, you also need the following qualities:
An ability to contribute to team-wide improvements while maintaining focus on personal achievement and responsibilities A passion to learn new skills and technologies Attention to grammatical detail, layout and presentation
This is a hybrid position. Expectation of days in office will be confirmed by your Hiring Manager. Qualifications Basic Qualifications * 2 or more years of work experience with a Bachelor's Degree or an Advanced Degree (e.g. Masters, MBA, JD, MD, or PhD)(e.g. Computer Science, Physics, Mathematics, Engineering) Preferred Qualifications * 3 or more years of work experience with a Bachelor's Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) * Experience in applying machine learning algorithms to real world data * You have experience in implementing statistical models and analytical algorithms in software * Prior experience in Python, Java, R or other programming language for data analysis, machine learning or algorithm development * Technical and analytical skills with the ability to pick up new technologies and concepts quickly * Problem solving skills (especially in data-centric applications) * Strong, clear, concise written and verbal communication skills * Ability to manage and prioritize personal workload * Practical experience of the handling and mining of large, diverse, data sets * Constructive participation in system architecture/design discussions from an analytical perspective * A Ph.D. or other postgraduate qualification would be an advantage but is not essential * Experience working in a Linux command line environment * Experience using SQL to analyze data * Experience with version control software and workflows (e.g. git) * You are comfortable working in a client facing environment U.S. Applicants Only The estimated salary range for this positionis $ to $ USD per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity.Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401(k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program. Work Hours Varies upon the needs of the department. Travel Requirements This position requires travel 5-10% of the time. Mental/Physical Requirements This position will be performed in an office setting. The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers. Visa is an EEO Employer Qualified applicants will receive consideration for employment without regard to race, color religion, sex, national origin, sexual orientation, gender identity, disability or protect veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with the EEOC guidelines and applicable local law.
  • Austin, Texas, United States

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