iVisa

Senior Data Scientist

12 November 2024
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Deadline date:
£65000 - £120000 / year

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

Team Summary

Visa Consulting & Analytics (VCA) is Visa’s consulting division, serving Visa’s clients (including card issuers, acquirers and merchants) and solving their strategic problems, focused on improving performance and profitability. Drawing on our expertise in strategy consulting, payments, data analytics, marketing, operational and macroeconomics, VCA drives high impact projects with tangible financial results.

What a Data Science Manager, VCA does at Visa:

The Data Science Manager is a key member of the Consulting and Analytics team, responsible for developing Data Analytics solutions to solve complex business problems by working with large data sets using quantitative techniques and building complex statistical models that learn from big data. In this highly collaborative role, you will work across multiple teams and functions to develop cutting-edge, creative, and advanced analytic solutions and processes. Together with other team members, you will design and deliver projects using appropriate analytic methodologies and techniques to address clients’ business objectives, collaborating closely with business stakeholders to understand the problems and determine the most suitable analytic approaches that provide meaningful results.

The role is focused on Taiwan and will report into Analytics & Data Products lead based in Shanghai.

Responsibilities include delivering projects on time and within scope, utilizing an in-depth knowledge of data analytics and advanced data mining techniques, as well as employing predictive, classification, and other analytic algorithms for modeling and segmentation. These analyses are essential for corroborating or refuting stated hypotheses and are incorporated into final client-facing solutions. The team continuously creates and protects analytic IP resulting from project learning.

Key Responsibilities include:

  • 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.
  • 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. Interacting with several internal and external stakeholders for the strategic definition of analysis and initiatives.
  • Continuously develop and present innovative ideas 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.
  • Support transfer technical knowledge to facilitate implementation of the business solution provided.
  • Document all projects developed, including clear and efficient coding, and write other documentation as needed.

Qualifications

What you will need:

  • 7-10 years of work experience and a Bachelor’s Degree or 6 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD).
  • Previous exposure (minimum of 5 years of work experience) to financial services/banking, credit cards or retailer/merchant analytics.
  • Ability to integrate data from various sources for comprehensive risk assessments.
  • 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.
  • Advanced knowledge of data visualization software such as Tableau and Power BI.
  • Excellent project management, organizational and presentational skills.
  • Knowledge of Agile methodology and scrum practices.
  • Ability to multi-task various projects while meeting required deadlines.
  • Strong teamwork, relationship management and interpersonal skills.
  • Proficient in Chinese and English (spoken/written).

What will also help:

  • Proven experience in delivering growth for financial services products.
  • Proven experience in Risk Management, particularly in Credit or Fraud Risk, within a Financial Institution.

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.