Remote Data Science Engineer Jobs
Remote Data Science Engineer jobs are open across the U.S. in sectors like technology, financial services, and healthcare, at remote-first companies and distributed engineering teams that hire from anywhere. Employers hiring remotely right now include AbbVie, Known, and Centrl. Find a role that fits below and apply directly.
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Showing 5 of 66+ Remote Data Science Engineer jobs
Who we are
More efficient. More accurate. More accessible. Exol is bringing industry-leading automation to businesses of all sizes through an innovative warehouse-as-a-service model.
What we need
Exol is seeking for a Senior Director, Data Science to join our Data Science team within our technology organization. Your job will be to build and lead a critical new data science capability, establishing the strategy, team, and roadmap that bring AI, advanced analytics, and intelligent decision-making into Exol’s technology platform and operations.
What we do
Exol’s technology platform brings together physical robotics, cloud technology, engineering, and operational capabilities. The Data Science team will add a new core capability focused on making that platform increasingly intelligent, efficient, and scalable through applied AI, machine learning, optimization, predictive analytics, and advanced data techniques.
What you'll do
- Build the data science function from the ground up, defining its strategy, priorities, operating model, and roadmap.
- Develop and execute a practical AI and data science strategy focused on improving the intelligence and efficiency of Exol’s platform.
- Identify high-value opportunities to apply machine learning, AI, optimization, predictive analytics, and advanced data techniques across the business.
- Partner with engineering, technology, operations, and commercial leaders to turn complex business and operational challenges into scalable, data-driven solutions.
- Build, mentor, and lead a high-performing team of data scientists, machine learning specialists, and related technical talent as the organization scales.
- Establish the standards, tools, processes, and governance necessary to move data science solutions from experimentation into reliable production environments.
- Serve as a senior advisor to Exol leadership on how AI and data can drive operational efficiency and competitive advantage.
What you'll need
- Minimum of 10 years of management experience and 15 years of total work experience
- Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Operations Research, or a related quantitative discipline. Master’s degree or PhD preferred.
- Significant leadership experience in data science, AI, machine learning, advanced analytics, or related technical disciplines, ideally in complex technology or operational environments.
- Demonstrated experience building or substantially scaling a data science organization or capability, rather than solely inheriting an established team.
- Strong knowledge of applied machine learning, AI, optimization, predictive modeling, and data-driven decision systems.
- Experience bringing data science solutions into production environments where reliability, scalability, and measurable business outcomes matter.
- Strong business judgment and communication skills, with the ability to prioritize investments, recruit technical talent, and communicate sophisticated technical concepts and strategic trade-offs to executive and nontechnical audiences.
Our Environment
- Up to 30% of travel may be required. Employees must have a valid driver's license and the ability to drive and/or fly to client locations and company HQ.
- Employees may be required to use a personal credit card for business travel expenses, which are reimbursed based on the program guidelines. Eligible employees may receive a corporate credit card based on role and travel requirements, but a personal credit card may be needed during onboarding until the corporate card is issued.
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About Exol
Exol provides flexible and scalable outsourced warehouse services to meet the dynamic needs of the modern supply chain. We operate state-of-the-art distribution centers, allowing you to focus on your business while we handle the complexities of warehouse operations. For more information, visit www.exol.com.
Who we are
More efficient. More accurate. More accessible. Exol is bringing industry-leading automation to businesses of all sizes through an innovative warehouse-as-a-service model.
What we need
Exol is seeking for a Senior Director, Data Science to join our Data Science team within our technology organization. Your job will be to build and lead a critical new data science capability, establishing the strategy, team, and roadmap that bring AI, advanced analytics, and intelligent decision-making into Exol’s technology platform and operations.
What we do
Exol’s technology platform brings together physical robotics, cloud technology, engineering, and operational capabilities. The Data Science team will add a new core capability focused on making that platform increasingly intelligent, efficient, and scalable through applied AI, machine learning, optimization, predictive analytics, and advanced data techniques.
What you'll do
- Build the data science function from the ground up, defining its strategy, priorities, operating model, and roadmap.
- Develop and execute a practical AI and data science strategy focused on improving the intelligence and efficiency of Exol’s platform.
- Identify high-value opportunities to apply machine learning, AI, optimization, predictive analytics, and advanced data techniques across the business.
- Partner with engineering, technology, operations, and commercial leaders to turn complex business and operational challenges into scalable, data-driven solutions.
- Build, mentor, and lead a high-performing team of data scientists, machine learning specialists, and related technical talent as the organization scales.
- Establish the standards, tools, processes, and governance necessary to move data science solutions from experimentation into reliable production environments.
- Serve as a senior advisor to Exol leadership on how AI and data can drive operational efficiency and competitive advantage.
What you'll need
- Minimum of 10 years of management experience and 15 years of total work experience
- Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Operations Research, or a related quantitative discipline. Master’s degree or PhD preferred.
- Significant leadership experience in data science, AI, machine learning, advanced analytics, or related technical disciplines, ideally in complex technology or operational environments.
- Demonstrated experience building or substantially scaling a data science organization or capability, rather than solely inheriting an established team.
- Strong knowledge of applied machine learning, AI, optimization, predictive modeling, and data-driven decision systems.
- Experience bringing data science solutions into production environments where reliability, scalability, and measurable business outcomes matter.
- Strong business judgment and communication skills, with the ability to prioritize investments, recruit technical talent, and communicate sophisticated technical concepts and strategic trade-offs to executive and nontechnical audiences.
Our Environment
- Up to 30% of travel may be required. Employees must have a valid driver's license and the ability to drive and/or fly to client locations and company HQ.
- Employees may be required to use a personal credit card for business travel expenses, which are reimbursed based on the program guidelines. Eligible employees may receive a corporate credit card based on role and travel requirements, but a personal credit card may be needed during onboarding until the corporate card is issued.
#LI-MB1
#LI-Remote
About Exol
Exol provides flexible and scalable outsourced warehouse services to meet the dynamic needs of the modern supply chain. We operate state-of-the-art distribution centers, allowing you to focus on your business while we handle the complexities of warehouse operations. For more information, visit www.exol.com.
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Find JobsRemote Data Science Engineer Job Market
Who's Hiring
Top Industries Hiring
- Technology & Software
- Retail
- Insurance
- Medical Devices
- Science & Research
What Employers Look For
The qualifications that appear most often in remote data science engineer jobs.
- Proficiency in Python with experience building production-grade data and ML pipelines
- Hands-on experience with distributed computing frameworks such as Apache Spark or Flink
- Experience deploying and monitoring machine learning models in cloud environments like AWS, GCP, or Azure
- Familiarity with MLOps tooling including feature stores, model registries, and workflow orchestrators
- Bachelor's or master's degree in computer science, data engineering, statistics, or a related field
- Experience with containerization and orchestration tools such as Docker and Kubernetes
Tips for Your Remote Data Science Engineer Job Search
Apply early to remote roles that fit
Migrate Mate lists remote data science engineer openings from across the U.S. in one place, so you can find roles that match your skills and apply directly without sorting through listings mixed with on-site or hybrid work.
Build a portfolio that shows end-to-end ownership
Remote employers can't watch you work, so your portfolio does the talking. Publish projects that go from raw data to a deployed model or production pipeline, with clear documentation explaining your decisions, tradeoffs, and results.
Prove async communication in your application
Distributed teams run on written communication. Write detailed, structured cover notes and include a README-style project summary in your application materials that shows you can explain technical work clearly to engineers and non-technical stakeholders alike.
Target remote-first companies with distributed engineering teams
Remote-first technology companies and distributed product teams hire data science engineers remotely as a default, not an exception. Look for companies whose engineering blogs, job postings, and team pages describe fully distributed or async-first cultures rather than hybrid arrangements.
Remote Data Science Engineer Jobs: Frequently Asked Questions
How do I get a remote data science engineer job?
Remote data science engineer roles go to candidates who can demonstrate technical depth and independent execution without in-person oversight. Remote-first companies and distributed product teams screen heavily for async written communication, self-directed project management, and hands-on fluency with tools like Python, SQL, Spark, and cloud ML platforms. A portfolio of end-to-end projects, clear documentation, and evidence you've shipped models that drove measurable outcomes gives you a concrete edge over candidates who lack remote work examples.
Which companies hire remote data science engineers?
Employers currently hiring remote data science engineers include AbbVie, Known, and Centrl, per current remote listings on Migrate Mate as of November 2026. Remote data science engineer roles concentrate at remote-first technology companies, distributed fintech and healthtech teams, and enterprise software firms that run globally distributed engineering organizations.
Can you get a remote data science engineer job with no experience?
Yes, but remote entry-level data science engineer roles are harder to land because employers expect you to contribute independently from day one without on-site mentorship. Early-career candidates who break in typically target remote-first startups, build a public portfolio of end-to-end ML or data pipeline projects, and demonstrate strong async communication through thorough documentation and clear write-ups. Open-source contributions and a completed capstone that shows production-ready thinking open more doors than a degree alone.
Do you need a degree for remote data science engineer jobs?
Not always. Many remote employers weigh a strong project portfolio, demonstrated proficiency in Python, SQL, and ML frameworks, and evidence of shipped work more heavily than a specific degree. A relevant bachelor's or master's in computer science, statistics, or a related field still appears in most job postings, but candidates without one regularly compete successfully by showing real results, published work, and measurable contributions to data or ML systems.
Which industries hire the most remote data science engineers?
Most remote data science engineer openings sit in Technology & Software, Retail, and Insurance, per current remote listings on Migrate Mate as of November 2026. These sectors hire data science engineers remotely because their core products, research, and analytics infrastructure are fully digital and can be built and maintained by distributed teams working across time zones.
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