Remote Data Science Analyst Jobs
Remote Data Science Analyst jobs are in active demand across the U.S., with remote-first firms and distributed teams hiring across technology, finance, healthcare, and retail analytics. Employers posting remote roles 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 Analyst 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.
See All 66 Remote Data Science Analyst Jobs
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Find JobsRemote Data Science Analyst 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 analyst jobs.
- Proficiency in Python or R for data analysis and statistical modeling
- Strong SQL skills for querying and manipulating large relational datasets
- Experience with data visualization tools such as Tableau or Power BI
- Bachelor's degree in statistics, computer science, mathematics, or a related field
- Familiarity with machine learning libraries such as scikit-learn or TensorFlow
- Experience communicating analytical findings clearly to non-technical stakeholders
Tips for Your Remote Data Science Analyst Job Search
Build a portfolio that proves async delivery
Remote employers want evidence you can take a vague question and return a clear, documented analysis without back-and-forth. Publish end-to-end projects on GitHub with a written narrative explaining your methodology and findings, not just code.
Signal remote readiness in every application
Remote hiring managers scan for clues that you've worked independently before. Call out async tools you've used, such as Notion, Confluence, or Jira, and mention any distributed team experience in your cover letter or work history, even from freelance or volunteer projects.
Apply early to remote roles that fit
Migrate Mate lists remote data science analyst openings from across the U.S. in one place, so you can find roles that match your skills and apply directly without bouncing between multiple sites.
Sharpen written communication for remote interviews
Remote data science analyst interviews often include a take-home case or async video screen before any live call. Practice writing up your analytical findings as short, executive-style summaries, because your written clarity is part of what remote teams are hiring for.
Remote Data Science Analyst Jobs: Frequently Asked Questions
How do I get a remote data science analyst job?
Remote data science analyst roles go to candidates who can demonstrate independent execution and clear written communication, because you won't have a manager walking the floor. Remote employers screen heavily for proficiency in Python or R, SQL, and data visualization tools like Tableau or Power BI. A portfolio of end-to-end projects, even from personal or open-source work, shows you can move from raw data to insight without hand-holding.
Which companies hire remote data science analysts?
Remote data science analyst roles are posted by AbbVie, Known, and Centrl and others right now, based on current remote listings on Migrate Mate as of November 2026. The hiring mix includes remote-first technology firms, distributed fintech and healthtech companies, and enterprise retailers with centralized analytics teams that operate across time zones.
Can you get a remote data science analyst job with no experience?
Yes, but remote entry-level roles are harder to land than in-office equivalents because you're expected to manage your own workflow from day one. Remote-first startups and smaller analytics consultancies are the most open to entry-level candidates. A portfolio of self-directed projects, a Kaggle competition record, or a published notebook demonstrating real analysis gives hiring managers something concrete to evaluate in the absence of prior job titles.
Do you need a degree for remote data science analyst jobs?
Not always. Many remote employers care more about what you can do with data than where you studied. A degree in statistics, computer science, or a quantitative field is common among hired candidates, but remote hiring managers frequently weigh demonstrated skills, a strong project portfolio, and fluency with tools like Python, SQL, and cloud data platforms as heavily as formal credentials.
Which industries hire the most remote data science analysts?
Remote data science analyst roles concentrate in Technology & Software, Retail, and Insurance, based on current remote listings on Migrate Mate as of November 2026. Those sectors favor remote data science analysts because their data infrastructure is cloud-hosted and their analytics teams are built to collaborate asynchronously across distributed locations.
See All 66 Remote Data Science Analyst Jobs
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