Data Science Analyst

1 June 2024
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Job Description

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

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

  • Develop and deploy analytical models and techniques within the organization and VCA’s clients including issuers, acquirers and merchants.

  • 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.

  • Develop and validate advance analytics models, algorithms, and other capabilities to solve business problem.

  • Enhance and optimize codes that scale critical business processes.

  • Develop and validate advanced ML algorithms, and other capabilities to solve business problem. Experience doing ML using R, Python (scikit-learn, etc.) or other similar software.

  • Design and develop dashboards using Tableau or Power BI.

  • Utilize Visa’s data and analytic capabilities, technology, and industry expertise to develop, standardized and implement the consulting analytical solutions.

  • Identify relevant market trends by country, based on a deep analysis of payment industry information.

  • Interact with several internal and external stakeholders for the strategic definition of analysis and initiatives.

  • Find opportunities to create and automate repeatable analysis 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

  • Perform client-specific analysis on portfolio data including proprietary information, such as customer demographics, activity, spend levels and financial information.

  • Communicate complex concepts and the results of the analyses in a clear and effective manner.

  • Support transfer technical knowledge to facilitate implementation of the business solution provided.

  • Support the implementation of complex models and data pipelines on large datasets.

  • Document all projects developed, including clear and efficient coding, and write other documentation as needed.

  • Identify and share best practices for key topics.

This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs.

Qualifications

Basic qualifications

  • 2 years of work experience with a Bachelor’s Degree (eg: Statistics, Computer Science, Engineering or other related fields) or at least 1 year of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD)

Preferred Qualifications

  • 3 years of work experience with a Bachelor’s Degree (eg: Statistics, Computer Science, Engineering or other related fields) or at least 2 year 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 developing Machine Learning models is a plus (Random Forest, Gradient Boosting, SVM, ANN) using Python (scikit-learn), R, Spark MLlib.
  • Hands-on Experience with data visualization and tools like Tableau and Power BI.
  • Translate data analysis insights to a business language.
  • Skills in 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.
  • Fluency in English (spoken/written).

Additional Information

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.