Data Scientist Jobs in USA with Visa Sponsorship
Data science is one of the strongest categories for H-1B visa sponsorship, with most positions requiring a master's degree or higher in a quantitative field. STEM classification makes extended OPT available, and sponsored roles are concentrated in tech, finance, and healthcare. For detailed occupation requirements, see the O*NET profile.
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Get Access To All JobsINTRODUCTION
We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam.
We are the Data team within Plaid’s Fraud organization. We build the machine learning systems that power Plaid’s fraud detection products, leveraging Plaid’s network data to help identify and prevent fraud before it happens. Our team owns the end-to-end ML lifecycle, from feature pipelines and model training to production serving and monitoring, ensuring our systems are reliable, scalable, and built to support hundreds of customers and data partners.
ROLE AND RESPONSIBILITIES
As a Data Scientist on the Fraud Data team, you will analyze customer and network traffic to understand how Plaid Protect performs across a range of use cases and customer segments. You’ll build dashboards and metrics that provide a clear, shared view of product performance, run backtests to evaluate performance and identify high-impact rules and model strategies, and generate insights that support customer growth and expansion. You’ll also design scalable data models and schemas to enable reliable analysis and reporting, while partnering closely with Product and Engineering to design and analyze experiments for new customer-facing features.
- Work at the intersection of product analytics, machine learning, and fraud and risk to uncover insights that improve product performance.
- Own the metrics, dashboards, and experiments that inform product strategy and decision-making.
BASIC QUALIFICATIONS
3–5 years of relevant experience, including at least 2–3 years working extensively with product analytics, experimentation, or data-driven products.
Strong proficiency in SQL and Python, with experience analyzing complex datasets and translating insights into action.
Hands-on experience with product analytics, experimentation, and/or backtesting methodologies.
Experience building and maintaining dashboards, reporting frameworks, and core product metrics.
* Strong communication and stakeholder management skills, with the ability to translate complex analyses into clear, actionable insights for technical and non-technical audiences.
PREFERRED QUALIFICATIONS
Experience in fraud/risk domains
Experience with developing ML models
Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid!
Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at accommodations@plaid.com. Please review our Candidate Privacy Notice here.
Additional compensation in the form(s) of equity and/or commission are dependent on the position offered. Plaid provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.
COMPENSATION RANGE
- Compensation Range: $176.4K - $226.8K
INTRODUCTION
We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam.
We are the Data team within Plaid’s Fraud organization. We build the machine learning systems that power Plaid’s fraud detection products, leveraging Plaid’s network data to help identify and prevent fraud before it happens. Our team owns the end-to-end ML lifecycle, from feature pipelines and model training to production serving and monitoring, ensuring our systems are reliable, scalable, and built to support hundreds of customers and data partners.
ROLE AND RESPONSIBILITIES
As a Data Scientist on the Fraud Data team, you will analyze customer and network traffic to understand how Plaid Protect performs across a range of use cases and customer segments. You’ll build dashboards and metrics that provide a clear, shared view of product performance, run backtests to evaluate performance and identify high-impact rules and model strategies, and generate insights that support customer growth and expansion. You’ll also design scalable data models and schemas to enable reliable analysis and reporting, while partnering closely with Product and Engineering to design and analyze experiments for new customer-facing features.
- Work at the intersection of product analytics, machine learning, and fraud and risk to uncover insights that improve product performance.
- Own the metrics, dashboards, and experiments that inform product strategy and decision-making.
BASIC QUALIFICATIONS
3–5 years of relevant experience, including at least 2–3 years working extensively with product analytics, experimentation, or data-driven products.
Strong proficiency in SQL and Python, with experience analyzing complex datasets and translating insights into action.
Hands-on experience with product analytics, experimentation, and/or backtesting methodologies.
Experience building and maintaining dashboards, reporting frameworks, and core product metrics.
* Strong communication and stakeholder management skills, with the ability to translate complex analyses into clear, actionable insights for technical and non-technical audiences.
PREFERRED QUALIFICATIONS
Experience in fraud/risk domains
Experience with developing ML models
Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid!
Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at accommodations@plaid.com. Please review our Candidate Privacy Notice here.
Additional compensation in the form(s) of equity and/or commission are dependent on the position offered. Plaid provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.
COMPENSATION RANGE
- Compensation Range: $176.4K - $226.8K
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Get Access To All JobsTips for Finding Visa Sponsorship as a Data Scientist
Specialize in a high-demand machine learning area
Natural language processing, computer vision, recommendation systems, and causal inference are specializations with strong sponsorship demand. Companies filing H-1B petitions for data scientists often need specific ML expertise that is difficult to source domestically, which strengthens the specialty occupation argument.
Target FAANG and top-tier tech companies
Google, Meta, Amazon, Apple, Netflix, and Microsoft file among the highest numbers of H-1B petitions for data science roles. These companies have streamlined immigration processes, dedicated legal teams, and the budget to support sponsorship at scale.
Publish research or contribute to open-source ML projects
Publications at conferences like NeurIPS, ICML, or KDD and contributions to open-source ML libraries demonstrate expertise that goes beyond a resume. This track record can also support future O-1 or EB-1 petitions if you build a significant body of work over time.
Use STEM OPT strategically
Data science degrees in statistics, computer science, or applied mathematics qualify for the 24-month STEM OPT extension, giving you up to 36 months of work authorization. Use this time to ship production ML models and demonstrate measurable business impact, which gives your employer a strong basis for sponsorship.
Frequently Asked Questions
How strong is visa sponsorship demand for data scientists?
Data scientist roles have consistently high H-1B visa filing activity, particularly in tech, finance, and healthcare. The role falls under SOC code 15-2051 (Data Scientists), which is classified as a STEM occupation. Companies like Google, Meta, Amazon, Netflix, and major banks file hundreds of H-1B petitions annually for data science positions.
How to find Data Scientist jobs with visa sponsorship?
Use Migrate Mate to find Data Scientist positions with H-1B, O-1 visa, or TN visa sponsorship. Focus on tech companies, financial institutions, healthcare organizations, and consulting firms that actively sponsor international talent. Filter for roles requiring machine learning, statistical analysis, and programming skills. Many Fortune 500 companies and growing startups regularly sponsor visas for qualified data science professionals.
What degree level is typically required for sponsored data scientist positions?
Most sponsored data scientist positions require at least a master's degree in statistics, computer science, mathematics, or a related quantitative field. Some entry-level roles accept a bachelor's degree with strong research or internship experience. A PhD can open doors to research scientist positions and may qualify for EB-1B or O-1 visa categories based on outstanding research contributions.
Can data scientists pursue green card sponsorship?
Yes, data scientists with several years of experience are strong candidates for EB-2 or EB-3 employer-sponsored green cards. Those with published research, patents, or significant contributions to the field may also qualify for EB-2 NIW (National Interest Waiver), which does not require employer sponsorship. Advanced degrees and specialized expertise in areas like machine learning or NLP can strengthen the petition.
What programming languages are most important for sponsored data science roles?
Python is the dominant language for data science, followed by R for statistical analysis and SQL for data manipulation. Experience with frameworks like PyTorch, TensorFlow, scikit-learn, and PySpark is expected for machine learning roles. Companies also value familiarity with cloud ML platforms like AWS SageMaker, Google Vertex AI, or Azure ML.
What is the prevailing wage requirement for sponsored Data Scientist jobs?
When a U.S. employer sponsors a foreign worker for a work visa, they are legally required to pay at least the "prevailing wage" — the average wage paid to workers in the same occupation, in the same geographic area, with similar experience. This is set by the Department of Labor to prevent employers from hiring foreign workers at below-market rates. The prevailing wage varies significantly by role, location, and experience level — for example, a data scientist in California will have a different prevailing wage than the same role in a smaller state. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search.