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Remote Data Science Jobs in Vermont (NOW HIRING)

ABB

Business Process Manager

Burlington, VT · Remote

This is a remote position, with preference for candidates to be located in a major metro city in ... Partner with senior leadership on FICO strategy, data integrity, internal controls, and roadmap ...

Athenahealth

Manager, Actuarial Analytics

Burlington, VT · Remote

$114K - $194K/yr

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 ...

Athenahealth

Manager, Actuarial Analytics

Burlington, VT · Remote

$114K - $194K/yr

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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All JobsData Science JobsRemote Data Science JobsRemote Data Science Jobs in Vermont

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.
More about Remote Data Science jobs
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:
Remote Data Science jobs near you
Silicon Photonic (SiPh) Test Engineer - Principal Engineer Test Engineering.

Silicon Photonic (SiPh) Test Engineer - Principal Engineer Test Engineering.

Globalfoundries

Essex Junction, VT • On-site, Remote

$85K - $146K/yr

Full-time

Posted 18 days ago

GlobalFoundries rating

8.2

Company rating: 8.2 out of 10

Based on 34 frontline employees who took The Breakroom Quiz

79th of 518 rated manufacturers

Job description

About GlobalFoundries:

GlobalFoundries is a leading full-service semiconductor foundry providing a unique combination of design, development, and fabrication services to some of the world's most inspired technology companies. With a global manufacturing footprint spanning three continents, GlobalFoundries makes possible the technologies and systems that transform industries and give customers the power to shape their markets. For more information, visit www.gf.com.


Summary of Role:
GlobalFoundries (GF) is seeking a self-driven professional to develop leading-edge test solutions for high-speed, electro-optic Silicon Photonics (SiPh) integrated circuit designs in the growing Data Center, High-performance Computing markets using next-generation GF proprietary technologies. The successful candidate will be a member of an established world-class test engineering team, driven by collaborative innovation, analytical thinking and creative problem solving.
Essential Responsibilities:

  • Develop wafer & module level custom test solutions for high-speed, photonic integrated circuits (PIC) based on GF proprietary systems or built on commercially available ATEs.

  • Interface with GF internal & client design teams to define product test requirements, design hardware consisting of probe cards & probe interface boards, and write programs to test PICs, which may contain a combination of high-speed, RF and optical circuits.

  • Collaborate across internal functional teams to bring development solutions to high-volume manufacturing and to drive continued yield improvements.

  • Full-time position at GF state-of-the-art SiPh Lab in Essex Junction, VT with some level of remote work flexibility.

  • Perform all activities in a safe and responsible manner and support all Environmental, Health, Safety & Security requirements and programs.

Other Responsibilities:

Perform all activities in a safe and responsible manner and support all Environmental, Health, Safety & Security requirements and programs.


Required Qualifications:

  • MSc in Physics, Electrical Engineering, Optical Engineering, Computer Science, or related field.

  • Background in characterization techniques for S-Parameter and Optical measurements.

  • Strong hands-on engineering with excellent debugging skills.

  • Advanced Java or C++ Programming in a Linux environment.

  • Basic understanding of silicon photonic, high-speed & mm-wave circuit design.

  • Proficient communication skills both written & verbal.

  • Demonstrated analytical & positive thinking, desire to innovate, accountability for your work and people skills.

Preferred Qualifications:

  • PhD in Physics or Electrical Engineering.

  • 2+ year experience developing test solutions for high-speed, RF/mmWave, electro-optic products.

  • PCB board design with emphasis on high-speed, low noise and matching techniques.

  • 2+ year direct design experience in electro-optic applications such as modulators, Lidar, or multiplexing circuits.

  • Fluency in shell scripting, multi-paradigm (Matlab/R) and high-level programming languages (Python/Perl) for automation and statistical data analysis.

  • Theoretical knowledge and 2+ year experience using Electro-Magnetic simulation tools.

  • Mastery of verbal and written communication to successfully interact with highly technical teams, engage with highly versed clients and to provide documentation of the highest quality.

  • Embrace the "push the envelope" approach, while living naturally curious lives and enjoying the process to venture into uncharted waters.

Expected Salary Range

$85,000.00 - $146,000.00

The exact Salary will be determined based on qualifications, experience and location.

If you need a reasonable accommodation for any part of the employment process, please contact us by email at usaccommodations@gf.com and let us know the nature of your request and your contact information. Requests for accommodation will be considered on a case-by-case basis. Please note that only inquiries concerning a request for reasonable accommodation will be responded to from this email address.

An offer with GlobalFoundries is conditioned upon the successful completion of pre-employment conditions, as applicable, and subject to applicable laws and regulations.

GlobalFoundries is fully committed to equal opportunity in the workplace and believes that cultural diversity within the company enhances its business potential. GlobalFoundries goal of excellence in business necessitates the attraction and retention of highly qualified people. Artificial barriers and stereotypic biases detract from this objective and may be illegally discriminatory.

All policies and processes which pertain to employees including recruitment, selection, training, utilization, promotion, compensation, benefits, extracurricular programs, and termination are created and implemented without regard to age, ethnicity, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, sexual orientation, gender identity or expression, veteran status, or any other characteristic or category specified by local, state or federal law

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