Manager, Data Science & Analytics Consulting

About Us

Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid.

At Visa, you'll have the opportunity to create impact at scale - tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world.

Join Visa and do work that matters - to you, to your community, and to the world. Progress starts with you.

Job Description

Responsibilities:

• Manage and deliver analytics projects from conception to completion with actionable insights and recommendations
• Define detailed scope and methodology, design and create solutions, and execute on the framework leveraging appropriate tools and techniques
• Actively seek out opportunities to innovate by using VisaNet, non-traditional data and new modelling techniques fit for purpose to the needs of our clients
• Enhance existing analytic techniques by promoting new methodology and best practices in analytics
• Develop metrics and use dashboards to quantify current state and to monitor progress across markets and segments using consistent definitions
• Act as data science advocate within our partners, advising and coaching analytical teams and sharing best practices and case studies.
• Collaborate with cross-functional teams to build and automate re-usable and scalable solutions.

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

hiring manager.

Qualifications

Basic Qualifications:

• 5+ years experience plus a Bachelor’s degree in an analytical field such as data science, computer science, computer engineering, mathematics, or similar others (graduate degree is a plus)
• Python: Experience with common ML libraries and PySpark, familiarity with developing in Jupyter notebooks
• ML techniques: Strong experience with XGBoost; solid understanding of training, validation, and test splits, as well as optimal feature selection
• ML training lifecycle: Proficiency in data hygiene, EDA patterns, hypothesis formulation, sampling, and model outcome reporting (e.g. VDR and false positive rates)
• Hands-on in developing machine learning solutions, delivering end-to-end data science projects, scaling up data solutions (Must have)
• Proficiency in statistical techniques such as Regression, Decision Trees, Random Forests, Neural Networks, etc.
• Proficiency in data mining and modeling techniques like Predictive Modeling, Classification, and Decision Trees.
• Proficient in big data aggregation using Hive, Spark, SQL, R/Python, and familiar with typical deep learning toolkits and packages (Must have)
• Competence in Excel and BI Tools such as PowerPoint or Tableau.
• Outstanding problem-solving skills, with demonstrated ability to think creatively and strategically
• Strong internal team and external client stakeholder management with a collaborative, diplomatic, and flexible style, able to work effectively in a matrixed organization
• Exhibit intellectual curiosity and strive to continually learn, self-motivated and results oriented individual with the ability to handle numerous projects
• Experience in planning, organizing, and managing multiple analytic projects with diverse cross-functional stakeholders (Must have)

Good-to-have Qualifications:

• Cloud: Experience with AWS (or other cloud environments) and the ability to ramp up quickly
• Experience in developing and applying Generative AI and Agentic AI solutions
• Experience in geospatial data analysis
• Banking /Payment /e-Commerce industry experiences are not desired but preferred.

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.