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
Are you skilled at turning hard numbers into compelling stories and useful strategic insights? Do you solve complex data challenges with creative flair? Put those skills to work answering strategic questions for one of the world's most respected and innovative payments companies.
In this role, you will be responsible for a range of duties from basic data analytics, to implementing and delivering advanced machine learning models, visualization solutions and high impact business projects. You will get chance to leverage your business acumen, programming skills, technical knowledge of big data and machine learning techniques. This function is critical in building market-relevant fraud solutions for our clients and intellectual property for Visa.
The position will be based at Atalanta, GA or Washington DC
Essential Functions
- Build and validate predictive models with advanced machine learning techniques and tools to drive business value, interpret and present modeling and analytical results to non-technical audience
- Write predictive model software packages for production deployment, support model installations, monitor and calibrate production models
- Conduct statistical analyses on various internal and external data sources with big data tools like Hadoop and Spark to identify interesting and valuable insights and trends, produce visualization and reports to internal business and product customers
- Develop insights from data into products using advanced statistical and machine learning methods
- Find opportunities to create and automate repeatable analyses or build self-service tools for business users
- Support sales and marketing efforts with sound statistical and financial analysis, execute ad-hoc analyses to meet the fast-changing market demands
- Develop business requirements and appropriate statistical analysis/prototypes to meet critical business needs
- Derive and develop new data attributes/features for modeling to grow analytic products
- Work on cross functional teams and collaborate with internal and external stakeholders
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)
- 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)
- A Master’s Degree in a quantitative field, such as Statistics, Mathematics, Operational Research, Computer Science, Economics, or engineering or Bachelor Degree with 2 years’ experience
- Successful internships or 6 month of experience in a predictive modeling function
- Preference given to candidates with multiple years working experience in predictive modeling functions
- Candidates with a PhD in a quantitative field, such as Statistics, Mathematics, Operational Research, Computer Science, Economics, or engineering preferred
- Strong background in two or more of the following areas: machine learning/AI algorithms, computations/statistical learning theory, scalable systems (e.g. Spark, Hadoop), large scale data analysis, optimization, functional analysis and deep learning.
- Experience with a range advanced techniques and emerging approaches to big data and data science (Python, Spark, TensorFlow, H2O, Dask, etc),extensive experience with SAS/SQL/Hive for extracting and aggregating data
- Good oral and written communication skills and attention to details
- Must be a team-player and capable of handling multi-tasks in a dynamic environment
- Visa and financial/payment industry knowledge or previous experience with fraud modeling is a plus, but not required
- Proficiency in Python programming language
- Proficiency in Python data analysis, modeling building and visualization libraries
- Proficiency with SQL
- Experience with Spark is a plus
- Experience with Unix/Linus script and shell programming is a plus
- Experience with SAS is a plus but not required
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 protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.
Visa will consider for employment qualified applicants with criminal histories in a manner consistent with applicable local law, including the requirements of Article 49 of the San Francisco Police Code.
U.S. APPLICANTS ONLY: The estimated salary range for a new hire into this position is 106,700 to 159,550 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. #J-18808-Ljbffr