Senior Data Scientist, AI Solutions Engineering - Client Services
Visa is hiring a Senior Data Scientist, AI Solutions Engineering - Client Services in Austin, United States. It pays $133k-$213k a year and Level rates it ; you can apply on Level.
AI in this role
Senior Data Scientist in AI Solutions Engineering designs data-driven machine learning and generative AI solutions for Client Services at Visa.
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
Overview:
The Sr. Data/AI Solutions Engineer role will be responsible for driving data-driven decision making across the organization. They will collaborate with business stakeholders, understand their problems, and design data-based solutions for them by making data available from new sources, build robust data models, creates and optimizes data enrichment pipelines, and provides engineering support to specific projects. This is a technical role that acts as a force multiplier and other data users across Client Services.
This role requires hands-on expertise on Data Engineering and AI/ML solutions. The role requires hands-on experience with large-scale data sets, building scalable models, and applying machine learning and statistical techniques to solve business problems. The position involves collaborating with cross-functional teams, translating analytics output into actionable recommendations, and communicating complex concepts to diverse audiences.
All roles require AI fluency, including the ability to work with emerging technologies such as Generative AI/Agentic AI tools (e.g. Agentic Toolchain, frontier models) to support everyday work.
Key Responsibilities:
- Deliver small to large-scale data engineering initiatives independently or as part of a cross-functional project team.
- Design, develop, and maintain scalable data models, schema designs, semantic layers, and certified datasets for efficient storage, retrieval, reporting, and analytics.
- Develop and implement advanced data science models, including deep learning, machine learning, recommendation systems, and generative models.
- Create visualizations to communicate complex data and insights in a clear and effective manner.
- Lead and provide direction to technical data science teams, ensuring high-quality and rigorous project outcomes.
- Implement data pipelines using modern data engineering frameworks and platforms such as Spark, Python, SQL, Airflow, dbt, cloud-native data services, and distributed processing technologies.
- Work with large-scale datasets using technologies such as Hadoop/Hive, Spark, Presto/Trino, Python, SQL, cloud data warehouses, and distributed query engines.
- Collaborate with cross-functional teams (product, engineering, marketing) to gather requirements and deliver scalable solutions.
- Support modern cloud-based data platforms across AWS, Azure, or Google Cloud Platform, including cloud data storage, compute, orchestration, monitoring, and security patterns.
- Translate analytics output into actionable business recommendations and communicate results to senior business audiences.
- Manage end-to-end data science projects, including planning, organizing, and delivering results with diverse teams.
- Work with real-world, large-scale data sets to build and deploy scalable models.
- Utilize modern distributed systems and data science tools (e.g., Hadoop, Hive/SQL, Apache Spark, TensorFlow, PyTorch, scikit-learn).
- Ensure reproducibility and quality in analytic pipelines and project deliverables.
Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager.
Qualifications
Basic Qualifications:
- 5+ years of relevant work experience with a bachelor’s degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD, OR 8+ years of relevant work experience.
Preferred Qualifications:
- Experience in developing advanced data science models and applying machine learning techniques to business problems.
- Experience in managing data science projects from scoping to delivery.
- Experience in extracting and aggregating data from large data sets using SQL or other tools.
- Experience in creating reproducible analytic pipelines.
- Experience in data visualization using Tableau, Power BI, or R/Python.
- Experience in working with modern distributed systems, including Hadoop, Hive/SQL, and Apache Spark.
- Experience in collaborating with cross-functional teams to deliver scalable solutions.
- Experience in communicating complex technical concepts to business audiences.
- Experience in leading project teams and providing technical direction.
- Extensive experience working in the data science, data engineering, or analytics profession.
- Hands-on experience working with extremely large data sets and building scalable models.
- Expertise in multiple programming languages (e.g., Python, R, Spark).
- Experience working in global organizations and collaborating with stakeholders across geographies.
- Previous exposure to financial services or payments industry is a plus but not mandatory.
Information for US Applicants
Work Hours
Varies upon the needs of the department.
Travel Requirements
This position requires travel 5-10% of the time.
Mental/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.
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 protect veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with the EEOC guidelines and applicable local law.How we rate this
Senior Data Scientist, AI Solutions Engineering - Client Services at Visa rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where data engineering was part of your work. What did you do?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where deep learning was part of your work. What did you do?
- Tell me about a project where data science was part of your work. What did you do?
- Tell me about a project where data modeling was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Data Engineering, Machine learning, Deep learning, Data Science, and Data Modeling. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
Want an expert to read your CV for this job?
Free. Send your CV and the role you want next. We reply by email within 2 to 4 business days.
Get new data scientist jobs (Builds AI ●●●●) by email
One email a week with the new data scientist jobs (Builds AI ●●●●), each rated for how much AI is in the work. No recruiter spam, unsubscribe in one click.
Free. One email a week. Unsubscribe in one click.
Similar roles
Data roles that build AI, at other companies.
What kind of AI work fits you?
Answer 12 practical questions in about three minutes. Get a simple profile, the work it points to, and live roles to explore next.
Find my next step