Data Science Manager Jobs in USA with Visa Sponsorship
Data Science Manager positions frequently qualify for H-1B, O-1, and EB-2 visa sponsorship due to the advanced statistical modeling, machine learning expertise, and team leadership requirements. Most roles require a master's degree in data science, statistics, computer science, or related quantitative field. For detailed occupation requirements, see the O*NET profile.
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As a Data Science Manager (DSM), you will lead a team of economists, scientists, and data engineers working to solve complex scientific problems that have high business and customer impact. You will be responsible for building structural and predictive models, leveraging data science workflows, and driving innovations that deliver measurable results for Amazon customers.
Key job responsibilities
- Leadership & Team Management: Independently manage and develop a diverse science team, creating an environment that enables consistent delivery and innovation; Build and maintain a high-performing team that can operate effectively and autonomously; Drive strategic growth opportunities for team members, providing paths to demonstrate higher-level scope, impact, and leadership; Establish clear performance metrics and audit mechanisms to track and communicate team progress; Foster a team culture focused on bringing research to production and delivering customer value
- Technical & Scientific Direction: Partner with stakeholders and leadership to define and execute the scientific vision for your team; Lead the development of structural and predictive models, leveraging emerging technologies and novel features; Drive the implementation of data science workflows and simulation frameworks; Bridge the gap between science, technology, and business requirements; Leverage the broader Amazon scientific community to enhance team capabilities and knowledge sharing
- Strategic Planning & Execution: Define and maintain team structure, strategic direction, and owned technologies; Establish processes that enable consistent delivery and quality of scientific artifacts; Drive reasonable schedules and adjust priorities to ensure optimal outcomes; Create and implement audit mechanisms to track team performance against goals; Remove roadblocks and optimize team productivity
- Communication & Influence: Create well-written documents to effectively communicate with technical and non-technical audiences; Influence science and analytics practices across the organization; Build strong partnerships with stakeholders across different business units; Present complex scientific findings to senior leadership; Drive adoption of best practices and innovative solutions
About the team
The Central Science Team within Amazon’s People Experience and Technology org (PXTCS) uses economics, behavioral science, statistics, machine learning, and Generative AI to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, well-being, and the value of work to Amazonians. We are an interdisciplinary team, which combines the talents of science and UX to develop and deliver solutions that measurably achieve this goal.
BASIC QUALIFICATIONS
- 5+ years of building quantitative solutions as a scientist or science manager experience
- 2+ years of scientists or machine learning engineers management experience
- 5+ years of applying statistical models for large-scale application and building automated analytical systems experience
- PhD in computer science, mathematics, statistics, machine learning or equivalent quantitative field
- Knowledge of Python or R or other scripting language
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
- Experience in Database like NoSQL, or experience in SQL Server/MySQL and experience in software development
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with data modeling, warehousing and building ETL pipelines
PREFERRED QUALIFICATIONS
- Experience with one of the following areas: machine learning technologies, Reinforcement Learning, Deep Learning, Computer Vision, Natural Language Processing (NLP) or related applications
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience operating large data warehouses
- Experience hiring, developing, and managing high-performing technical teams
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $142,300/year in our lowest geographic market up to $272,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
DESCRIPTION
As a Data Science Manager (DSM), you will lead a team of economists, scientists, and data engineers working to solve complex scientific problems that have high business and customer impact. You will be responsible for building structural and predictive models, leveraging data science workflows, and driving innovations that deliver measurable results for Amazon customers.
Key job responsibilities
- Leadership & Team Management: Independently manage and develop a diverse science team, creating an environment that enables consistent delivery and innovation; Build and maintain a high-performing team that can operate effectively and autonomously; Drive strategic growth opportunities for team members, providing paths to demonstrate higher-level scope, impact, and leadership; Establish clear performance metrics and audit mechanisms to track and communicate team progress; Foster a team culture focused on bringing research to production and delivering customer value
- Technical & Scientific Direction: Partner with stakeholders and leadership to define and execute the scientific vision for your team; Lead the development of structural and predictive models, leveraging emerging technologies and novel features; Drive the implementation of data science workflows and simulation frameworks; Bridge the gap between science, technology, and business requirements; Leverage the broader Amazon scientific community to enhance team capabilities and knowledge sharing
- Strategic Planning & Execution: Define and maintain team structure, strategic direction, and owned technologies; Establish processes that enable consistent delivery and quality of scientific artifacts; Drive reasonable schedules and adjust priorities to ensure optimal outcomes; Create and implement audit mechanisms to track team performance against goals; Remove roadblocks and optimize team productivity
- Communication & Influence: Create well-written documents to effectively communicate with technical and non-technical audiences; Influence science and analytics practices across the organization; Build strong partnerships with stakeholders across different business units; Present complex scientific findings to senior leadership; Drive adoption of best practices and innovative solutions
About the team
The Central Science Team within Amazon’s People Experience and Technology org (PXTCS) uses economics, behavioral science, statistics, machine learning, and Generative AI to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, well-being, and the value of work to Amazonians. We are an interdisciplinary team, which combines the talents of science and UX to develop and deliver solutions that measurably achieve this goal.
BASIC QUALIFICATIONS
- 5+ years of building quantitative solutions as a scientist or science manager experience
- 2+ years of scientists or machine learning engineers management experience
- 5+ years of applying statistical models for large-scale application and building automated analytical systems experience
- PhD in computer science, mathematics, statistics, machine learning or equivalent quantitative field
- Knowledge of Python or R or other scripting language
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
- Experience in Database like NoSQL, or experience in SQL Server/MySQL and experience in software development
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with data modeling, warehousing and building ETL pipelines
PREFERRED QUALIFICATIONS
- Experience with one of the following areas: machine learning technologies, Reinforcement Learning, Deep Learning, Computer Vision, Natural Language Processing (NLP) or related applications
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience operating large data warehouses
- Experience hiring, developing, and managing high-performing technical teams
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $142,300/year in our lowest geographic market up to $272,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
How to Get Visa Sponsorship as a Data Science Manager
Emphasize advanced analytics leadership
Highlight experience managing data science teams, implementing ML pipelines, and driving strategic decisions through predictive modeling to demonstrate the specialized management skills that justify visa sponsorship.
Document quantitative impact metrics
Present specific examples of revenue increases, cost savings, or efficiency gains from your data science initiatives to show measurable business value that supports your sponsorship case.
Target tech companies and consulting firms
Focus on employers like Google, Microsoft, McKinsey, or Deloitte that regularly sponsor visas for senior data roles and understand the strategic value of data science leadership.
Highlight cross-functional collaboration skills
Emphasize experience translating complex analytics into business insights for executives and coordinating with product, engineering, and marketing teams to demonstrate your unique management capabilities.
Showcase advanced technical expertise
Document proficiency in specialized tools like TensorFlow, PyTorch, cloud platforms, and statistical programming languages that require years of training and aren't easily replaceable domestically.
Consider the EB-2 pathway early
Data Science Manager roles often qualify for EB-2 green cards due to the advanced degree requirement and national interest potential, making it worth discussing with sponsors.
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Get Access To All JobsFrequently Asked Questions
Do Data Science Manager roles typically get H-1B sponsorship?
Yes, Data Science Manager positions regularly receive H-1B sponsorship because they require specialized knowledge in statistical modeling, machine learning algorithms, and advanced analytics that qualifies as a specialty occupation. The combination of technical expertise and management responsibilities makes these roles strong sponsorship candidates.
What degree do I need for Data Science Manager visa sponsorship?
Most employers require a master's degree in data science, statistics, computer science, mathematics, or a related quantitative field. Some accept a bachelor's degree with significant additional experience, but the master's requirement is increasingly common and strengthens your sponsorship case significantly.
Can I qualify for an O-1 visa as a Data Science Manager?
Data Science Managers can qualify for O-1 visas if they have extraordinary achievements like published research in top journals, patents, speaking at major conferences, or leading groundbreaking projects at recognized companies. The role alone isn't enough, you need documented exceptional accomplishments.
Which companies sponsor Data Science Managers most frequently?
Large tech companies (Google, Amazon, Microsoft), consulting firms (McKinsey, Deloitte, BCG), financial institutions (Goldman Sachs, JPMorgan), and healthcare companies (UnitedHealth, Anthem) sponsor Data Science Manager roles regularly. These employers understand the strategic value and have established sponsorship processes.
How does team size affect my sponsorship chances?
Managing larger data science teams generally strengthens your sponsorship case by demonstrating senior-level responsibilities that are harder to fill domestically. However, even managers of small teams can qualify if the technical complexity and business impact of your work is significant enough.
What is the prevailing wage requirement for sponsored Data Science Manager jobs?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.
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