Data Engineer - Visa Consulting & Analytics

  • Full-time
  • Job Family Group: Product Development

Company Description

As the world's leader in digital payments technology, Visa's mission is to connect the world through the most creative, reliable and secure payment network - enabling individuals, businesses, and economies to thrive. Our advanced global processing network, VisaNet, provides secure and reliable payments around the world, and is capable of handling more than 65,000 transaction messages a second. The company's dedication to innovation drives the rapid growth of connected commerce on any device, and fuels the dream of a cashless future for everyone, everywhere. As the world moves from analog to digital, Visa is applying our brand, products, people, network and scale to reshape the future of commerce.

At Visa, your individuality fits right in. Working here gives you an opportunity to impact the world, invest in your career growth, and be part of an inclusive and diverse workplace. We are a global team of disruptors, trailblazers, innovators and risk-takers who are helping drive economic growth in even the most remote parts of the world, creatively moving the industry forward, and doing meaningful work that brings financial literacy and digital commerce to millions of unbanked and underserved consumers.

You're an Individual. We're the team for you. Together, let's transform the way the world pays.

Job Description

Visa Consulting and Analytics (VCA), the consulting arm of Visa, is a global team of industry experts in strategy, marketing, operations, risk and economics consulting, with decades of experience in the payments industry.

Our VCA teams offers:

  • Consulting services customized to the needs of Visa client’s business objectives and strategy
  • Business and economic insights and perspectives that impact business and investment decisions
  • Self-service digital solutions Visa clients can leverage to improve performance in product, marketing and operations
  • Proven data-driven marketing strategies to increase clients’ ROI

 VCA team is looking for an individual to join our consulting practice and play a role in the data science team. The ideal candidate is adept at using large data sets to address key strategic needs for Visa’s clients including issuers, acquirers and merchants. He/She must have experience using a variety of data mining/data analysis methods, using a variety of data tools and implementing models, using/creating algorithms and creating/running simulations. He/She must have a proven ability to drive business results with their data-based insights. Adept at creative and critical thinking, be able to deconstruct problems and transform insights into large scale, state-of-the-art solutions.

Responsibilities

  • Work with large volumes of data; extract and manipulate large datasets using standard tools such as Hadoop (Hive), Spark, Python (pandas, NumPy), SAS, SQL, etc.
  • Hands-on skills in cleaning, manipulating, analyzing, and visualizing large data sets.
  • Data Cleansing/Wrangling – This involve parsing and aggregating messy, incomplete, and unstructured data sources to produce data sets that can be used in analytics/predictive modeling.
  • Utilize Visa's data and analytic capabilities, technology, and industry expertise to develop, standardized and implement the consulting analytical solutions.
  • Find opportunities to create and automate repeatable analyses or build streamlined solutions for business consultant and Visa’s clients.
  • Continuously develop and present innovative ideas based on data driven approach in order to improve current business practices within Visa
  • Communicate complex concepts and the results of the analyses in a clear and effective manner.
  • Document all projects developed, including clear and efficient coding, and write other documentation as needed.
  • Identify and share best practices for key topics.

Qualifications

Basic Qualifications:

  • 2 years of work experience with a Bachelor’s Degree or an Advanced Degree (e.g. Masters, MBA, JD, MD, or PhD)

Preferred Qualifications:

  • 3 or more years of work experience or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD)
  • Experience in retail banking, payments, financial services, and/or technology industries is a plus. Strong interest in the future of payments is a must.
  • Hands-on experience extracting and manipulate large datasets (Big Data) using standard tools such as Hadoop (Hive), Spark, Python (pandas, NumPy), SAS (E. Guide, Macro programming), SQL, etc.
  • Hands-on experience in advanced analytics and statistical modeling including Linear Regression, Logistic Regression, Clustering methods (e.g. K-means), Classification models, among others.
  • Hands-on Experience with data visualization and tools like Tableau and Power BI.
  • Translate data analysis insights to a business language.
  • Continuously develop and present innovative ideas based on data driven approach in order to improve current business practices within Visa.
  • Excellent project management, organizational and presentational skills.
  • Knowledge of Agile methodology and scrum practices.
  • Proven ability to quickly learn and apply new techniques.
  • Ability to multi-task various projects while meeting required deadlines.
  • Strong teamwork, relationship management and interpersonal skills.
  • Results oriented.
  • Bilingual Spanish/English (spoken/written).

Additional Information

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, and reach with hands and arms.

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

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