OPT Data Scientist Jobs
Data Scientist roles are among the most actively sponsored positions for F-1 OPT students, with strong demand across tech, finance, and healthcare. Most positions qualify under STEM OPT, giving you up to three years of work authorization. A background in machine learning, Python, or statistical modeling significantly strengthens your candidacy.
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WHAT IS THE OPPORTUNITY?
As a Data Scientist you will problem solve, analyze, design, implement and monitor machine learning applications using state of the art tools and algorithms. As part of the US Wealth Management Applied AI team, your day-to-day work will include many exciting fields in applied statistics and machine learning, including causal inference and experimentation, time-series forecasting, predictive marketing and advertising, and model interpretation.
WHAT WILL YOU DO?
- Collaborate with key business partners and stakeholders to understand business objectives/opportunities and problem statements in order to provide solutions that align to business needs that are actionable with a tangible outcome
- Prepare, analyze, and transform data from structured and unstructured sources
- Develop, implement, and deploy statistical and ML models at scale
- Leverage visualization tools/packages to story-tell and to convey data-driven insights with actionable recommendations to key stakeholders
- Quickly learn new methods, tools and technologies presented in research communities to implement, adapt and innovate
- Effectively communicate findings to business partners and executives
- Developing predictive data models, quantitative analyses and visualization of targeted, big data sources
- Assist Senior Data Scientists throughout the ML lifecycle
- Perform offline model evaluation and validation
- Build dashboards and communicate insights
- Monitor production models for drift and performance
- Document experiments and support AI governance
- Present findings to technical and business stakeholders
WHAT DO YOU NEED TO SUCCEED?
Must have:
- Master’s or PhD in Computer Science, Statistics, Mathematics, or Physics
- 2-3 years of experience in data solutions and applying data techniques
- Strong knowledge of design, development, and implementation experience utilizing data science technologies
- 3+ years of experience in machine learning, predictive analytics, and statistical modeling
- Experience with causal inference and experimentation, time-series forecasting, predictive marketing and advertising, and model interpretation
- Experience with libraries such as:
- ML/DL: sklearn, tensorflow, pytorch
- Analysis: pandas, pySpark, scala Spark, SQL, Hive
- Excellent analytical, problem solving, time management and organizational skills
- Experience delivering presentations to wide audiences, both technical and non-technical
- Basic understanding of Generative AI and LLMs
- Familiarity with RAG concepts
- Experience using OpenAI, Claude, Gemini, or Azure OpenAI APIs
- Understanding of prompt engineering
- Ability to evaluate LLM outputs
- Awareness of hallucinations and responsible AI
Nice-to-have:
- Good understanding of AWS Big Data services such as Amazon S3, EMR and Glue; and ML capabilities including Sagemaker
- Experienced with Jupyter Notebooks, IntelliJ, Visual Studio Code other notebook environments
- Experience with visualization tools such as Tableau, QuickSight, Looker
- Experience working in Unix/Linux environments
- Experience working as part of an agile team using Github and JIRA
- Experience with digital data collection tools such as Google Analytics
- Exposure to Snowflake, Databricks, Sparr, Power BI or Tableau
- MLflow, NLP, embeddings, semantic sea
- Feature stores and model monitoring, REST APIs and FastAPI
What’s in it for you?
We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.
- A comprehensive Total Rewards Program includes competitive compensation and flexible benefits, such as 401(k) program with company-matching contributions, health, dental, vision, life, disability insurance, and paid-time off
- Leaders who support your development through coaching and managing opportunities
- Ability to make a difference and lasting impact
- Work in a dynamic, collaborative, progressive, and high-performing team
- Opportunities to do challenging work
- Opportunities to build close relationships with clients
The expected salary range for this particular position is $80,000-$140,000 depending on your experience, skills, and registration status, market conditions and business needs.
You have the potential to earn more through RBC’s discretionary variable compensation program which gives you an opportunity to increase your total compensation, provided the business meets its performance targets and you meet your individual goals.
RBC’s compensation philosophy and principles recognize the importance of a highly qualified global workforce and plays a critical role in attracting, engaging and retaining talent that:
- Drives RBC’s high-performance culture
- Enables collective achievement of our strategic goals
- Generate sustainable shareholder returns and above market shareholder value
LI-POST
TECHPJ
Job Skills
Actuarial Modeling, Big Data Management, Commercial Acumen, Data Mining, Data Science, Decision Making, Machine Learning (ML), Natural Language Processing (NLP), Predictive Analytics, Python (Programming Language)
Additional Job Details
Address: 250 NICOLLET MALL:MINNEAPOLIS
City: Minneapolis
Country: United States of America
Work hours/week: 40
Employment Type: Full time
Platform: WEALTH MANAGEMENT
Job Type: Regular
Pay Type: Salaried
Posted Date: 2026-08-07
Application Deadline: 2026-08-28
Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above
Our Employment Opportunities
At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.
Join our Talent Community
Stay in-the-know about great career opportunities at RBC. Sign up and get customized info on our latest jobs, career tips and Recruitment events that matter to you.
Expand your limits and create a new future together at RBC. Find out how we use our passion and drive to enhance the well-being of our clients and communities at jobs.rbc.com.
RBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. Qualified applicants may be contacted to review their resume in more detail.
Job Description
WHAT IS THE OPPORTUNITY?
As a Data Scientist you will problem solve, analyze, design, implement and monitor machine learning applications using state of the art tools and algorithms. As part of the US Wealth Management Applied AI team, your day-to-day work will include many exciting fields in applied statistics and machine learning, including causal inference and experimentation, time-series forecasting, predictive marketing and advertising, and model interpretation.
WHAT WILL YOU DO?
- Collaborate with key business partners and stakeholders to understand business objectives/opportunities and problem statements in order to provide solutions that align to business needs that are actionable with a tangible outcome
- Prepare, analyze, and transform data from structured and unstructured sources
- Develop, implement, and deploy statistical and ML models at scale
- Leverage visualization tools/packages to story-tell and to convey data-driven insights with actionable recommendations to key stakeholders
- Quickly learn new methods, tools and technologies presented in research communities to implement, adapt and innovate
- Effectively communicate findings to business partners and executives
- Developing predictive data models, quantitative analyses and visualization of targeted, big data sources
- Assist Senior Data Scientists throughout the ML lifecycle
- Perform offline model evaluation and validation
- Build dashboards and communicate insights
- Monitor production models for drift and performance
- Document experiments and support AI governance
- Present findings to technical and business stakeholders
WHAT DO YOU NEED TO SUCCEED?
Must have:
- Master’s or PhD in Computer Science, Statistics, Mathematics, or Physics
- 2-3 years of experience in data solutions and applying data techniques
- Strong knowledge of design, development, and implementation experience utilizing data science technologies
- 3+ years of experience in machine learning, predictive analytics, and statistical modeling
- Experience with causal inference and experimentation, time-series forecasting, predictive marketing and advertising, and model interpretation
- Experience with libraries such as:
- ML/DL: sklearn, tensorflow, pytorch
- Analysis: pandas, pySpark, scala Spark, SQL, Hive
- Excellent analytical, problem solving, time management and organizational skills
- Experience delivering presentations to wide audiences, both technical and non-technical
- Basic understanding of Generative AI and LLMs
- Familiarity with RAG concepts
- Experience using OpenAI, Claude, Gemini, or Azure OpenAI APIs
- Understanding of prompt engineering
- Ability to evaluate LLM outputs
- Awareness of hallucinations and responsible AI
Nice-to-have:
- Good understanding of AWS Big Data services such as Amazon S3, EMR and Glue; and ML capabilities including Sagemaker
- Experienced with Jupyter Notebooks, IntelliJ, Visual Studio Code other notebook environments
- Experience with visualization tools such as Tableau, QuickSight, Looker
- Experience working in Unix/Linux environments
- Experience working as part of an agile team using Github and JIRA
- Experience with digital data collection tools such as Google Analytics
- Exposure to Snowflake, Databricks, Sparr, Power BI or Tableau
- MLflow, NLP, embeddings, semantic sea
- Feature stores and model monitoring, REST APIs and FastAPI
What’s in it for you?
We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.
- A comprehensive Total Rewards Program includes competitive compensation and flexible benefits, such as 401(k) program with company-matching contributions, health, dental, vision, life, disability insurance, and paid-time off
- Leaders who support your development through coaching and managing opportunities
- Ability to make a difference and lasting impact
- Work in a dynamic, collaborative, progressive, and high-performing team
- Opportunities to do challenging work
- Opportunities to build close relationships with clients
The expected salary range for this particular position is $80,000-$140,000 depending on your experience, skills, and registration status, market conditions and business needs.
You have the potential to earn more through RBC’s discretionary variable compensation program which gives you an opportunity to increase your total compensation, provided the business meets its performance targets and you meet your individual goals.
RBC’s compensation philosophy and principles recognize the importance of a highly qualified global workforce and plays a critical role in attracting, engaging and retaining talent that:
- Drives RBC’s high-performance culture
- Enables collective achievement of our strategic goals
- Generate sustainable shareholder returns and above market shareholder value
LI-POST
TECHPJ
Job Skills
Actuarial Modeling, Big Data Management, Commercial Acumen, Data Mining, Data Science, Decision Making, Machine Learning (ML), Natural Language Processing (NLP), Predictive Analytics, Python (Programming Language)
Additional Job Details
Address: 250 NICOLLET MALL:MINNEAPOLIS
City: Minneapolis
Country: United States of America
Work hours/week: 40
Employment Type: Full time
Platform: WEALTH MANAGEMENT
Job Type: Regular
Pay Type: Salaried
Posted Date: 2026-08-07
Application Deadline: 2026-08-28
Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above
Our Employment Opportunities
At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.
Join our Talent Community
Stay in-the-know about great career opportunities at RBC. Sign up and get customized info on our latest jobs, career tips and Recruitment events that matter to you.
Expand your limits and create a new future together at RBC. Find out how we use our passion and drive to enhance the well-being of our clients and communities at jobs.rbc.com.
RBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. Qualified applicants may be contacted to review their resume in more detail.
See all 402+ OPT Data Scientist Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new OPT Data Scientist Jobs.
Get Access To All JobsTips for Finding OPT Sponsorship as a Data Scientist
Lead with your STEM OPT eligibility
Mention your STEM OPT authorization upfront in your resume summary and cover letter. Employers who understand the 24-month extension are far more likely to engage than those assuming standard 12-month OPT timelines.
Target companies with active USCIS filing histories
Companies that regularly file H-1B visa petitions are experienced with work authorization requirements. Focus your applications on employers with a documented track record of sponsoring international data professionals, not just those with open roles.
Quantify your technical impact, not just your tools
Listing Python and SQL is table stakes. Describe the outcome: a model that reduced churn by 15%, or a pipeline that cut processing time in half. Measurable results make sponsorship conversations easier for hiring managers to justify.
Apply before your OPT clock creates urgency
Start applying at least three to four months before your current authorization expires. Employers notice tight timelines and may hesitate. Earlier outreach signals that you're organized and gives both sides room to negotiate terms.
Clarify your authorization status in your first email
When reaching out to recruiters, briefly state your OPT status and STEM extension eligibility in one sentence. Removing ambiguity early filters out employers who won't sponsor and saves you time with those who will.
Build a portfolio that removes doubt about your skills
A GitHub repository with real data projects, documented methodology, and clean code answers the question before it's asked. Recruiters for Data Scientist roles regularly check portfolios before scheduling interviews.
Data Scientist OPT: Frequently Asked Questions
Does a Data Scientist role qualify for STEM OPT extension?
Yes, Data Scientist positions almost always qualify for the 24-month STEM OPT extension. The role falls under CIP codes tied to computer science, statistics, and applied mathematics. Your degree must be in a STEM-designated field and your employer must enroll in E-Verify. Confirm your degree's CIP code with your DSO before applying.
How do I find Data Scientist jobs that sponsor OPT students?
Migrate Mate filters job listings specifically for employers willing to sponsor international candidates, including OPT students. Searching there saves significant time compared to applying broadly and discovering sponsorship limitations late in the process. Focus on companies in tech, finance, healthcare, and consulting, which have the highest concentration of sponsored Data Scientist roles.
Can I work as a Data Scientist on OPT before my employer files for H-1B?
Yes. OPT authorizes full-time employment in a role directly related to your degree field. You don't need an H-1B to start working. If your employer files an H-1B cap-subject petition before April 1 and you maintain valid OPT, the cap-gap rule protects your authorization through September 30 while the petition is pending.
What degree fields support OPT authorization for Data Scientist roles?
Computer Science, Statistics, Mathematics, Data Science, Information Systems, and Engineering degrees are the most common qualifying fields. Applied economics and quantitative social science degrees may also qualify depending on how your school's DSO classified the program. The key requirement is that your job duties must be directly related to your degree field.
Do I need to report a Data Scientist job to my DSO while on OPT?
Yes. Within 10 days of starting employment, you must report your employer's name, address, job title, and start date to your DSO, who updates your SEVIS record. Failing to report can jeopardize your OPT status. If you change employers or take on a second position, each change requires a separate update.