Data Scientist - Featurespace

Company Description

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid.

Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.

Job Description

At Visa, we are passionate about making a difference. We lead the way in disrupting fraud from multiple vectors. In this role you will be joining an exciting, innovative business new to the Visa family!

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 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 behaviours in real-time, based on retail, online and ecommerce transaction data.

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

This is a hybrid position. Expectation of days in office will be confirmed by your Hiring Manager.

Qualifications

Basic Qualifications
2+ years of relevant work experience and a Bachelors degree, OR 5+ years of relevant work experience

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)

Required experience:

• Good degree in a scientific or numerate discipline, e.g. Computer Science, Physics, Mathematics, Engineering or equivalent work experience
• Experience in applying practical machine learning algorithms to real-world data
• Experience in implementing statistical models and analytical algorithms in software
• Experience using Python, Java, R or another major 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 prioritise 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

Additional Information

Work Hours: Varies upon the needs of the department.

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