Client Consulting Manager

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

As a Senior Client Consulting Manager you will play a critical role in delivering data-driven insights and solutions that drive portfolio performance, enhance customer lifecycle outcomes, and optimize campaign effectiveness for our clients. This role is centered on leveraging advanced analytics to translate complex data into actionable strategies that influence real business decisions.

You will lead end-to-end analytics engagements—from problem framing and model development to deployment, monitoring, and business adoption—ensuring solutions are scalable and embedded into day-to-day decisioning. The role also offers exposure to AI and machine learning applications, supporting the development of production-ready solutions that create sustainable impact.

Responsibilities:

Conduct deep-dive analysis on large-scale transactions and customer data to generate actionable business insights

Build, validate, and interpret statistical and machine learning models (e.g., propensity, segmentation, forecasting, uplift)

Execute the end-to-end analytics workflow: problem framing, data exploration, feature engineering, modeling, and validation

Ensure analytical rigor, data quality checks, and QA on all deliverables

Translate analytical outputs into clear insights and recommendations for non-technical stakeholders

Support the deployment of data science models into production environments in partnership with engineering and platform teams

Contribute to model monitoring, performance tracking, and periodic recalibration

Leverage AI/ML techniques where appropriate to enhance scalability, automation, or personalization use cases

Create user-friendly dashboards, presentations, and executive-ready materials

Manage multiple analytics projects simultaneously, ensuring on-time delivery against the analytic plan

Maintain accurate project documentation and support internal and client reviews

Stay current with evolving analytics, ML, and AI techniques relevant to payments and consumer data

Evaluate new data sources, tools, and methodologies that can strengthen core data science outcomes

Share best practices and learnings across teams and markets

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

Qualifications

Bachelor’s degree in Economics, Finance, Computer Science, Statistics, or related quantitative field

6+ years of hands-on experience in data science, analytics, and feature engineering

Experience delivering analytics projects end-to-end in a fast-paced, client-facing environment

Experience supporting/owning deployment of AI/ML models in real‑world business contexts (production or pilot environments)

Strong proficiency in Python and data platforms (Hadoop, Hive, Impala, or cloud-based equivalents)

Solid understanding of statistical and ML techniques (regression, classification, clustering, tree-based models, etc.)

Familiarity with model deployment and ML lifecycle concepts is a plus, but not the primary requirement

Ability to explain complex analytical concepts clearly to non-technical audiences

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.