Senior Data Science Engineer Jobs in USA with Visa Sponsorship
Senior Data Science Engineer roles are among the most actively sponsored positions in the U.S. tech industry. Employers routinely file H-1B petitions for this title, and the specialty occupation requirement is straightforward to satisfy with a degree in computer science, statistics, or a related quantitative field. For detailed occupation requirements, see the O*NET profile.
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Get Access To All JobsINTRODUCTION
Hi, We’re AppFolio
We’re innovators, changemakers, and collaborators. We’re more than just a software company – we’re pioneers in cloud and AI who deliver magical experiences that make our customers’ lives easier. We’re revolutionizing how people do business in the real estate industry, and we want your ideas, enthusiasm, and passion to help us keep innovating.
We are looking for a Senior Data Science Engineer to join an evolving Business Data Platform team in the Data Science & Analytics Department. This role owns the design, quality, and lifecycle of GTM-focused data mart assets, including schema design, metric definitions, deprecation of legacy datasets, and semantic layer build out to power AI and BI use-cases that unlock reporting, activation, decision-making, and data democratization initiatives like Chat to Data for the business.
YOUR IMPACT
Collaborate to structure and derive more value out of our data across acquisition and growth efforts:
- Design and Maintain Data Pipelines that ingest data from important business systems to Snowflake via Fivetran. Establish SLAs based on business needs, and design pipelines and processes to meet them.
- Define and Deliver Shared Business Metrics by partnering with representatives across the business to align on metric definition and to deliver data mart models and semantic views to serve as the source of truth for tracking metrics.
- Lead migration efforts to drive adoption of your new gold standard Data Mart assets across our reporting layer through gaining an understanding of analytics requirements and business processes reliant on other data sources.
- Own the evergreen data transformation requirements of Business technologies, and curation of data for broad applicability.
- Partner cross-functionally to combine or create add-on services enablement to adoption funnel data models to power objectives for customer targeting and product upsell opportunities.
- Activate GTM Datasets created in the Business Data Platform back into Business Systems through reverse ETL Pipelines.
- Identify data quality issues and implement semantic data layer standards.
BASIC QUALIFICATIONS
Technical skills – Create and maintain data models, tables, and dashboards needed to manage and scale our Sales and Marketing teams.
- Business acumen – understands key challenges facing our business and partners with key stakeholders to find creative ways to apply data analytics to solve them; connects dots between data & business outcomes.
- Attention to detail – Proactively checks all work for errors and does not let important details slip when it comes to data and its accuracy.
- Cross-Functional Knowledge – Navigates across verticals and functions and understands how each department contributes to our mission. Able to build relationships and quickly establish trust with others to make things happen. Brings teams and people together to accomplish important things.
- Efficiency – able to quickly iterate on data generation and refinement. Looks for ways to improve processes to maximize efficiency and remove redundancy.
Must have
Minimum of 6+ years of work experience in Analytics Engineering, Data Engineering, Data Science, or Data Analytics.
- 6+ years of experience supporting analytical data requirements of core internal business applications.
- Full Stack Data Science experience: Demonstrated success in bridging the gap between high-level project requirements and complex application data.
- Data engineering: expertise in dbt, Snowflake, object-oriented programming, version control, and the technical skills to build and deploy model pipelines to production. Experience creating/maintaining widely adopted production tables.
- Data analysis, visualization, and exploration: Exploratory data analysis skills are a critical tool for every full-stack data science engineer, and the results help answer important business questions.
- Proficiency in SQL and Python-based (Pandas and/or Spark) approaches for data transformation.
- Communication – You have a wealth of experience helping teams make data-driven decisions.
LOCATION
Find out more about our locations by visiting our site.
COMPENSATION & BENEFITS
The compensation that we reasonably expect to pay for this role is: $138,400 - $173,000 base pay. The actual compensation for this role will be determined by a variety of factors, including but not limited to the candidate’s skills, education, experience, and internal equity.
Please note that compensation is just one aspect of a comprehensive Total Rewards package. The compensation range listed here does not include additional benefits or any discretionary bonuses you may be eligible for based on your role and/or employment type.
Regular full-time employees are eligible for benefits – see here.
LI-KB1
INTRODUCTION
Hi, We’re AppFolio
We’re innovators, changemakers, and collaborators. We’re more than just a software company – we’re pioneers in cloud and AI who deliver magical experiences that make our customers’ lives easier. We’re revolutionizing how people do business in the real estate industry, and we want your ideas, enthusiasm, and passion to help us keep innovating.
We are looking for a Senior Data Science Engineer to join an evolving Business Data Platform team in the Data Science & Analytics Department. This role owns the design, quality, and lifecycle of GTM-focused data mart assets, including schema design, metric definitions, deprecation of legacy datasets, and semantic layer build out to power AI and BI use-cases that unlock reporting, activation, decision-making, and data democratization initiatives like Chat to Data for the business.
YOUR IMPACT
Collaborate to structure and derive more value out of our data across acquisition and growth efforts:
- Design and Maintain Data Pipelines that ingest data from important business systems to Snowflake via Fivetran. Establish SLAs based on business needs, and design pipelines and processes to meet them.
- Define and Deliver Shared Business Metrics by partnering with representatives across the business to align on metric definition and to deliver data mart models and semantic views to serve as the source of truth for tracking metrics.
- Lead migration efforts to drive adoption of your new gold standard Data Mart assets across our reporting layer through gaining an understanding of analytics requirements and business processes reliant on other data sources.
- Own the evergreen data transformation requirements of Business technologies, and curation of data for broad applicability.
- Partner cross-functionally to combine or create add-on services enablement to adoption funnel data models to power objectives for customer targeting and product upsell opportunities.
- Activate GTM Datasets created in the Business Data Platform back into Business Systems through reverse ETL Pipelines.
- Identify data quality issues and implement semantic data layer standards.
BASIC QUALIFICATIONS
Technical skills – Create and maintain data models, tables, and dashboards needed to manage and scale our Sales and Marketing teams.
- Business acumen – understands key challenges facing our business and partners with key stakeholders to find creative ways to apply data analytics to solve them; connects dots between data & business outcomes.
- Attention to detail – Proactively checks all work for errors and does not let important details slip when it comes to data and its accuracy.
- Cross-Functional Knowledge – Navigates across verticals and functions and understands how each department contributes to our mission. Able to build relationships and quickly establish trust with others to make things happen. Brings teams and people together to accomplish important things.
- Efficiency – able to quickly iterate on data generation and refinement. Looks for ways to improve processes to maximize efficiency and remove redundancy.
Must have
Minimum of 6+ years of work experience in Analytics Engineering, Data Engineering, Data Science, or Data Analytics.
- 6+ years of experience supporting analytical data requirements of core internal business applications.
- Full Stack Data Science experience: Demonstrated success in bridging the gap between high-level project requirements and complex application data.
- Data engineering: expertise in dbt, Snowflake, object-oriented programming, version control, and the technical skills to build and deploy model pipelines to production. Experience creating/maintaining widely adopted production tables.
- Data analysis, visualization, and exploration: Exploratory data analysis skills are a critical tool for every full-stack data science engineer, and the results help answer important business questions.
- Proficiency in SQL and Python-based (Pandas and/or Spark) approaches for data transformation.
- Communication – You have a wealth of experience helping teams make data-driven decisions.
LOCATION
Find out more about our locations by visiting our site.
COMPENSATION & BENEFITS
The compensation that we reasonably expect to pay for this role is: $138,400 - $173,000 base pay. The actual compensation for this role will be determined by a variety of factors, including but not limited to the candidate’s skills, education, experience, and internal equity.
Please note that compensation is just one aspect of a comprehensive Total Rewards package. The compensation range listed here does not include additional benefits or any discretionary bonuses you may be eligible for based on your role and/or employment type.
Regular full-time employees are eligible for benefits – see here.
LI-KB1
How to Get Visa Sponsorship as a Senior Data Science Engineer
Lead with your technical stack, not just your title
Sponsors evaluate Senior Data Science Engineers on specific tools: PyTorch, TensorFlow, Spark, and SQL pipelines carry more weight than a generic resume. Listing exact frameworks signals you can contribute immediately and reduces employer hesitation around sponsorship cost.
Target companies with an established H-1B track record
Large tech firms and data-intensive companies in finance, healthcare, and logistics file H-1B petitions annually for this role. Focusing your search on employers with prior sponsorship history dramatically improves your odds of receiving and successfully completing an offer with visa support.
Clarify your OPT or current status early in conversations
Employers sponsor more readily when they understand your timeline. If you have STEM OPT remaining, say so upfront. It shows the employer has up to three years before H-1B sponsorship becomes necessary, which lowers their perceived risk and urgency considerably.
Quantify business impact, not just model accuracy
Hiring managers sponsoring senior roles want proof of ROI. Frame your experience around revenue protected, cost reduced, or decisions improved by your models. Concrete business outcomes make sponsorship feel like an investment with a clear return, not an administrative burden.
Understand the specialty occupation standard for your exact role
H-1B approval hinges on demonstrating your position requires a specific bachelor's degree or higher. For Senior Data Science Engineers, a degree in statistics, computer science, mathematics, or data science satisfies this cleanly. Roles blending general management duties can face added scrutiny from USCIS.
Use Migrate Mate to find roles that explicitly sponsor
Filtering for verified sponsoring employers saves weeks of guesswork. Migrate Mate surfaces Senior Data Science Engineer roles from companies actively willing to file H-1B or other work visa petitions, so you spend your time applying where sponsorship is already on the table.
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Get Access To All JobsFrequently Asked Questions
Does a Senior Data Science Engineer role qualify as an H-1B specialty occupation?
Yes, consistently. USCIS treats Senior Data Science Engineer as a specialty occupation because the position normally requires a bachelor's degree or higher in a specific technical field such as computer science, statistics, applied mathematics, or data science. The direct relationship between the degree field and the job duties is well-established, which means RFEs on specialty occupation grounds are less common for this title than for more generalist roles.
What degree do I need for an employer to sponsor my H-1B as a Senior Data Science Engineer?
A bachelor's degree or higher in computer science, statistics, mathematics, data science, or a closely related quantitative field satisfies the H-1B educational requirement for this role. Degrees in adjacent fields like electrical engineering or operations research can also qualify if your coursework covered statistical modeling or machine learning. A three-year Australian or Indian bachelor's degree is generally accepted as equivalent to a U.S. four-year degree, though some USCIS adjudicators may request a credential evaluation for clarity.
Which visa types are realistic for Senior Data Science Engineers seeking U.S. sponsorship?
The H-1B is the most common path and requires winning the annual lottery, which selects roughly 25% of registrations. Australians can pursue the E-3, which has no lottery and processes faster. Canadians and Mexicans qualify for the TN visa under the USMCA. Candidates with a demonstrated record of exceptional research or industry impact may qualify for the O-1A, which is cap-exempt and bypasses the lottery entirely. Migrate Mate lists roles by visa type so you can filter for employers open to your specific status.
Do large tech companies sponsor Senior Data Science Engineers more reliably than startups?
Generally, yes. Companies like Amazon, Google, Microsoft, and Meta have dedicated immigration teams, established relationships with immigration law firms, and predictable annual H-1B filing cycles. Startups can and do sponsor, but they face tighter cash constraints and sometimes lack internal expertise to manage the process. Mid-size companies with 500 or more employees and an existing engineering org tend to be the most reliable sponsors outside of major tech firms, since they have legal infrastructure without the bureaucracy that slows larger organizations.
Can I switch employers between the H-1B lottery and my start date without losing my status?
If your H-1B was approved and you're already working in H-1B status, you can transfer to a new employer under H-1B portability once the new employer files a transfer petition. However, if you won the lottery but your start date hasn't arrived yet, you're not yet in H-1B status and cannot use portability. In that scenario, switching employers requires the new employer to either file a cap-exempt petition if they qualify, or register you in the next lottery cycle.
What is the prevailing wage requirement for sponsored Senior Data Science Engineer 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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