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Remote Data Science Jobs in Vermont (NOW HIRING)

Sr. Tax Manager (REMOTE)

Montpelier, VT · On-site +1

$134K - $167K/yr

... designed to help scientists, researchers, and clinicians solve the worlds greatest health ... Experience using Excel macros, Power BI, Alteryx and/or similar data analysis/visualization tools ...

Technical Project Manager

Montpelier, VT · On-site +1

$50 - $62/hr

Remote Reference ID: JN -042026-106675 Date Posted: 05/29/2026 Shortcut: * Description ... Use Microsoft Excel for data analysis, tracking, and reporting. Experience Requirements: * 5 to 8 ...

These talented individuals, many of whom have specialized engineering or scientific expertise ... The role is a remote position; location base will be reviewed as this position covers all regions ...

The FP&A team partners across the business to turn financial data into actionable insights that ... Bachelor's degree in Actuarial Science, Statistics, Mathematics, or related field. * Associate of ...

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Showing results 1-20

Remote Data Science information

See Vermont salary details

$23.3K

$103.5K

$197.5K

How much do remote data science jobs pay per year?

As of Jun 15, 2026, the average yearly pay for remote data science in Vermont is $103,494.00, according to ZipRecruiter salary data. Most workers in this role earn between $53,459.00 and $143,549.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Data Scientist, and why are they important?

To thrive as a Remote Data Scientist, you need strong analytical skills, proficiency in statistics, and a solid background in mathematics or computer science, often supported by a relevant degree. Expertise in programming languages such as Python or R, familiarity with machine learning libraries, and experience with cloud-based data platforms are typically required. Excellent communication, self-motivation, and time management skills help you effectively collaborate and deliver results in a remote environment. These skills ensure accurate data analysis, meaningful insights, and successful teamwork despite physical distance.

How do remote data scientists typically collaborate with cross-functional teams to deliver insights?

Remote data scientists often work closely with product managers, engineers, and business analysts using digital collaboration tools such as Slack, Zoom, and project management platforms. Regular virtual meetings, code sharing via Git repositories, and clear documentation are essential to ensure alignment and transparency. While working remotely can present challenges in communication, proactive updates and scheduled syncs help foster strong teamwork and keep projects on track.

What is remote data science?

Remote data science refers to the practice of performing data analysis, modeling, and interpretation tasks from a location outside of a traditional office, such as from home or a co-working space. Remote data scientists use tools like Python, R, and SQL to analyze data, build predictive models, and communicate insights to stakeholders, all while collaborating virtually with their teams. This setup offers flexibility and can increase access to global job opportunities, but also requires strong self-motivation and communication skills to be effective.

Can a data scientist work fully remote?

Yes, many data scientists work fully remote, especially in companies that prioritize flexible work arrangements. Remote data science roles often require strong communication skills, proficiency with collaboration tools, and the ability to work independently on projects using programming languages like Python or R. However, some positions may require occasional in-person meetings or on-site presence depending on company policies.

Is 40 too late for data science?

Age is not a barrier to entering data science, and many professionals start or transition into the field later in life. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications, regardless of age.

Will AI replace data scientists?

AI is transforming the role of data scientists by automating routine tasks such as data cleaning and basic analysis, but it does not eliminate the need for human expertise in interpreting results, designing models, and making strategic decisions. Data scientists will continue to be essential for developing complex algorithms, understanding business context, and ensuring ethical use of AI tools. Skills in programming, statistical analysis, and machine learning remain critical for the profession's evolving landscape.

What Are the Qualifications to Get a Remote Data Science Job?

The qualifications for a remote data scientist depend in large part on your employer and their industry. Most employers expect remote data science professionals to have at least a bachelor’s degree in statistics, math, computer science, or a related field. Some expect postgraduate degrees in a field like data mining or machine learning or demonstrable skills in these areas. As a remote worker, you need access to relevant programs and an internet connection. You may also want to pursue certification, such as becoming a Certified Analytics Professional (CAP).

What is the difference between Remote Data Science vs Remote Data Analyst?

AspectRemote Data ScienceRemote Data Analyst
Required CredentialsDegree in Data Science, Statistics, or related field; programming skills in Python/R; knowledge of machine learningDegree in Statistics, Mathematics, or related field; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentCollaborative teams, research-focused, often involves building models and algorithmsData reporting, visualization, and interpreting data trends for decision-making
Employer & Industry UsageTech companies, finance, healthcare, e-commerceMarketing agencies, retail, finance, healthcare

Remote Data Science involves developing predictive models and advanced analytics, requiring programming and machine learning skills. Remote Data Analysts focus on interpreting data, creating reports, and visualizations. While both roles analyze data remotely, Data Scientists typically handle more complex modeling tasks, whereas Data Analysts focus on data interpretation and reporting.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or features. Data scientists often use this concept to focus on the most impactful variables, optimize models, and prioritize tasks for efficiency.
What are the most commonly searched types of Data Science jobs in Vermont? The most popular types of Data Science jobs in Vermont are:
What are popular job titles related to Remote Data Science jobs in Vermont? For Remote Data Science jobs in Vermont, the most frequently searched job titles are:
What job categories do people searching Remote Data Science jobs in Vermont look for? The top searched job categories for Remote Data Science jobs in Vermont are:
Senior Machine Engineer, ML Systems and Infrastructure

Senior Machine Engineer, ML Systems and Infrastructure

Autodesk

Montpelier, VT • Remote

$105K - $144K/yr

Other

Posted 8 days ago


Autodesk rating

9.5

Company rating: 9.5 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

7th of 190 rated software companies


Job description

Job Requisition ID #

26WD98118

POSITION OVERVIEW

The work we do at Autodesk touches nearly every person on the planet. By creating software tools for making buildings, machines, and even the latest movies, we influence and empower some of the most creative people in the world to solve problems that matter.

Autodesk is seeking a Senior ML Engineer, ML Systems and Infrastructure to design and scale the systems that enable machine learning across research and product development. You will help build the infrastructure behind large-scale data pipelines, distributed training systems, evaluation frameworks, and production ML workflows that support foundation models and ML-powered product features.

This role is ideal for an engineer who is deeply interested in scalable systems and production-grade ML infrastructure. You will operate independently across multiple parts of the stack and help define strong engineering practices for reliability, performance, and maintainability.

This role is fully remote-friendly, with team members distributed across the US and Canada.

Location: US or Canada Remote, East Coast

RESPONSIBILITIES

  • Design and build scalable systems for ML training, evaluation, deployment, and monitoring

  • Develop and improve data pipelines that process large-scale structured and semi-structured technical datasets

  • Optimize distributed workflows for performance, reliability, resource utilization, and cost efficiency

  • Build platform capabilities such as experiment tracking, model versioning, checkpointing, reproducibility, and observability

  • Contribute to model deployment, inference services, and production monitoring workflows

  • Improve data quality, lineage, provenance, and operational transparency across ML pipelines

  • Contribute to architecture and design discussions across the team

  • Identify and resolve bottlenecks in data, compute, orchestration, and observability layers

  • Mentor engineers through code reviews, design guidance, and knowledge sharing

  • Collaborate closely with researchers, product engineers, and platform partners to turn ML workflows into robust engineering systems

MINIMUM QUALIFICATIONS

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent industry experience

  • At least 3 to 4 years of industry experience building and operating production software, ML systems, distributed infrastructure, or large-scale data pipelines

  • Strong experience in software engineering, distributed systems, backend systems, or ML infrastructure

  • Strong proficiency in Python and experience delivering production-quality systems

  • Experience designing and operating scalable data or compute pipelines

  • Experience with cloud platforms such as AWS, Azure, or GCP

  • Familiarity with containers, CI/CD, observability, and release quality practices

  • Ability to independently drive technical execution on complex work with limited oversight

PREFERRED QUALIFICATIONS

  • Experience building data pipelines for large-scale structured and semi-structured technical datasets

  • Experience with data lineage, provenance, governance, and responsible data usage in ML systems

  • Experience with distributed data processing and orchestration systems such as Ray, Airflow, Spark, or similar platforms

  • Experience with model deployment, inference services, monitoring, and observability for production ML systems

  • Experience building ML-ready representations for geometry, graph, hierarchical, or multimodal data

  • Experience with distributed ML frameworks such as PyTorch, Lightning, DeepSpeed, FSDP, Megatron, or similar

  • Familiarity with AEC workflows, design data, BIM/CAD formats, or Autodesk products

THE IDEAL CANDIDATE

  • Thinks like a systems engineer and executes like a strong software developer

  • Can balance short-term delivery with long-term platform health

  • Brings strong technical judgment and ownership

  • Improves team effectiveness through mentoring and engineering rigor

  • Enjoys solving scaling, performance, and reliability challenges

At Autodesk, we're building a diverse workplace and an inclusive culture to give more people the chance to imagine, design, and make a better world. Autodesk is proud to be an equal opportunity employer and considers all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender, gender identity, national origin, disability, veteran status or any other legally protected characteristic. We also consider for employment all qualified applicants regardless of criminal histories, consistent with applicable law.

Are you an existing contractor or consultant with Autodesk? Please search for open jobs and apply internally (not on this external site). If you have any questions or require support, contact Autodesk Careers (Careers%20%3Ccareers@autodesk.com%3E) .


Autodesk logo

About Autodesk

Sourced by ZipRecruiter

Autodesk is changing how the world is designed and made. Our technology spans architecture, engineering, construction, product design, manufacturing, media, and entertainment, empowering innovators everywhere to solve challenges big and small. From greener buildings to smarter products to more mesmerizing blockbusters, Autodesk software helps our customers to design and make a better world for all. For more information visit autodesk.com or follow @autodesk.

Industry

Software development

Company size

10,000+ Employees

Headquarters location

San Rafael, CA, US

Year founded

1982