CoreWeaveLivingston, NJ / New York, NY / Sunnyvale, CA / Bellevue, WA$182k-$242kjust now
VisaPosted 1d ago
Forecasting Data Scientist at Visa scores 12 out of 100 on AI centrality, which makes it AI Level 1 of 4 (Little AI) on this board. The level measures how much of the work is AI, not seniority.
AI in this role
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
Role Summary:
The Data Scientist is responsible for solving complex business problems using advanced data science techniques, AI/ML models, and data-driven frameworks. This role develops and executes a vision for data science capabilities, leading the design and development of large-scale systems and fostering innovation within the team. The Data Scientist collaborates closely with cross-functional teams to integrate data science solutions, communicates technical concepts to stakeholders, and influences business decisions with actionable insights.
All roles require digital fluency, including the ability to work with emerging technologies such as Generative AI tools (e.g. ChatGPT, Microsoft Copilot) to support everyday work.
Key Responsibilities:
- Solve complex business problems using advanced data science techniques, AI/ML models, and frameworks.
- Develop and execute a vision for data science capabilities aligned with business goals.
- Lead the design and development of large-scale data science systems and foster innovation within the team.
- Apply advanced data science techniques and models to drive business impact and stay up-to-date with industry trends.
- Collaborate with cross-functional teams to integrate data science capabilities and communicate complex technical concepts to stakeholders.
- Develop and maintain expertise in multiple programming languages and data science tools.
- Identify opportunities for data science to drive business impact and present results to senior leadership and business partners.
Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager.
Qualifications
Basic Qualifications:
- 2 or more years of work experience with a bachelor’s degree or an Advanced Degree (e.g. Masters, MBA, JD, MD, or PhD).
Preferred Qualifications:
- 3 or more years of work experience with a bachelor’s degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD).
- Experience with time series forecasting methodologies, including classical approaches such as SARIMA/SARIMAX or Vector-Autoregression / Vector-Error-Correction, and advanced local/global forecasting methods such as N-HiTS, TFT, DeepAR, NeuralProphet, or similar techniques.
- Familiarity with emerging time series foundation models and generative forecasting approaches, such as TimesFM, TimeGPT, or related AI-driven forecasting tools, with a demonstrated ability to stay current with new developments in forecasting and applied machine learning.
- Experience incorporating AI and automation capabilities into regular data science workflows to improve forecasting accuracy, experimentation speed, model monitoring, optimization, scalability, and overall team efficiency.
- Experience in developing advanced data science models.
- Experience in multiple programming languages (e.g., Python, R, Spark).
- Experience with data science tools and technologies (e.g., TensorFlow, PyTorch, scikit-learn).
- Experience working with real-world data sets and building scalable models from large-scale data.
- Experience working with cross-functional teams (e.g., product, engineering, marketing).
- Experience in project management and meeting deadlines in a fast-moving environment.
- Experience working in global organizations and collaborating with stakeholders and development teams across regions.
- Experience in deep learning, machine learning, recommendation systems, generative models, and statistical analyses.
- Experience working with global organizations and roles requiring collaboration with stakeholders and partners worldwide.
- Previous exposure to financial services or payments industry.
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.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
- What's a project where you used ChatGPT hands-on?
- Walk me through how you've used Copilot in your day-to-day work.
- What are the limits of PyTorch that you've run into, and how did you work around them?
- What's a project where you used TensorFlow hands-on?
- Walk me through how you've used scikit-learn in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: ChatGPT, Copilot, PyTorch, TensorFlow, and scikit-learn. 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.
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