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Remote Data Science R Jobs in Danville, VT (NOW HIRING)

Revvity

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 ...

Maximus

Appian Developer

Montpelier, VT · Remote

This position is remote and requires a Public Trust security clearance. Maximus TCS (Technology and ... Perform SQL data modeling and database design. * Troubleshoot, debug, and optimize Appian ...

Maximus

Appian Developer

Barre, VT · Remote

This position is remote and requires a Public Trust security clearance. Maximus TCS (Technology and ... Perform SQL data modeling and database design. * Troubleshoot, debug, and optimize Appian ...

Maximus

Junior BUR and Storage Engineer

Barre, VT · Remote

This position is remote. Junior Backup, Restore & Storage Engineer supporting enterprise disaster ... across on‑premise, data center, and hybrid environments to ensure continuity of IT and OT ...

Maximus

Cloud Platform Engineer

Barre, VT · Remote

$54.75 - $73.25/hr

This is a remote position. Maximus is a trusted federal partner supporting mission‑critical ... ensuring data protection, recovery readiness, and compliance with enterprise and federal ...

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All JobsRemote Data Science R JobsRemote Data Science R Jobs in Danville, VT

Remote Data Science R information

See Danville, VT salary details

$37.1K

$121.3K

$194.2K

How much do remote data science r jobs pay per year?

As of Jul 6, 2026, the average yearly pay for remote data science r in Danville, VT is $121,323.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,400.00 and $134,400.00 per year, depending on experience, location, and employer.

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

AspectRemote Data Science RRemote Data Analyst
Required SkillsStatistical analysis, R programming, data modeling, machine learningData visualization, basic statistical analysis, Excel, SQL
CertificationsR certifications, data science certificates, possibly advanced degreesData analysis certifications, Excel, SQL courses
Work EnvironmentCollaborative teams, research projects, data science platformsReporting, dashboards, business insights
Industry UsageTech, finance, healthcare, research institutionsMarketing, retail, finance, operations

Remote Data Science R roles focus on advanced statistical modeling and machine learning using R, often requiring specialized certifications and working on complex data projects. Remote Data Analysts typically handle data reporting, visualization, and basic analysis to support business decisions. While both roles involve data handling, Data Science R positions demand deeper technical expertise and programming skills.

What are Remote Data Science R jobs?

Remote Data Science R jobs are positions that involve using the R programming language to analyze and interpret data, build statistical models, and generate insights, all while working from a remote location. These roles typically require strong skills in data manipulation, visualization, and statistical analysis using R. Professionals in these positions may work for companies in various industries, collaborating with teams online and leveraging cloud-based tools. Remote Data Science R jobs offer flexibility, allowing individuals to work from home or anywhere with a reliable internet connection.

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, expertise in statistics, programming (Python or R), and typically a degree in data science, computer science, or a related field. Familiarity with data analysis tools, machine learning frameworks (like TensorFlow or scikit-learn), and cloud platforms (such as AWS or Google Cloud) is commonly required. Outstanding problem-solving, self-motivation, and effective virtual communication skills help you excel in remote environments. These abilities are essential for deriving actionable insights from data and collaborating efficiently across distributed teams.

How do remote Data Science R professionals typically collaborate with cross-functional teams while working from different locations?

Remote Data Science R professionals often use a combination of communication platforms (like Slack, Microsoft Teams, or Zoom) and project management tools (such as Jira or Trello) to stay connected with colleagues in engineering, product management, and business analysis. Sharing code and models through version control systems (like Git) and documenting workflows in shared repositories helps maintain transparency and collaboration. Regular virtual meetings and presentations are crucial for aligning goals, discussing progress, and receiving feedback. This collaborative approach ensures that data-driven insights effectively support organizational objectives, even in a distributed work environment.
Remote Data Science R jobs near you
Generative AI Automation Engineer - Remote Job

Generative AI Automation Engineer - Remote Job

EnthuZiastic

Barre, VT • Remote

Full-time

Posted 14 days ago

Job description

About Us

Our mission is to bring people together and connect them into a community to nurture each other. We aim to share a conducive environment, a joyous space to grow and excel; a world brimming with selfless love and enough kindness. We strive to enrich each of our lives with kaleidoscopic memories we make here - vibrant, lively, of all hues and colors.

Job Description

​

This is a remote position.

We are seeking a highly skilled and innovative Generative AI Automation Engineer to join our team. The ideal candidate will be responsible for designing, developing, and implementing automation solutions powered by Generative AI models. This role requires a combination of expertise in machine learning, natural language processing, software engineering, and automation frameworks to drive efficiency and innovation in business processes.

Key Responsibilities:

Generative AI Model Implementation:

  • Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks.

  • Integrate pre-trained models or build custom models for specific use cases.

Automation Design and Development:

  • Design and implement AI-driven workflows and solutions to automate repetitive tasks and improve process efficiency.

  • Develop APIs, scripts, and tools for seamless integration of AI models into existing systems.

Data Management:

  • Collect, preprocess, and analyze large datasets for training and validating AI models.

  • Ensure data privacy and compliance with regulatory requirements during data handling.

System Integration:

  • Collaborate with software development and IT teams to integrate Generative AI solutions with enterprise systems.

  • Build and maintain pipelines for real-time AI inference and automation.

Monitoring and Optimization:

  • Continuously monitor AI automation solutions to ensure accuracy, efficiency, and reliability.

  • Optimize models and processes based on performance metrics and user feedback.

Research and Innovation:

  • Stay updated with the latest advancements in Generative AI and automation technologies.

  • Identify opportunities for implementing cutting-edge AI solutions to address business challenges.

Documentation and Collaboration:

  • Document technical designs, workflows, and implementation strategies.

  • Collaborate with cross-functional teams, including product managers, data scientists, and software engineers.

Requirements

Required Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

  • Strong programming skills in Python, with experience in frameworks like TensorFlow, PyTorch, or Hugging Face.

  • Proficiency in designing and deploying machine learning models, particularly in Generative AI.

  • Experience with automation tools (e.g., RPA, workflow orchestration tools).

  • Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and containerization technologies (Docker, Kubernetes).

  • Solid understanding of data structures, algorithms, and software design principles.

  • Strong analytical and problem-solving skills.

  • Excellent communication and teamwork abilities.

Preferred Qualifications:

  • Experience with NLP, image generation, or multimodal AI models.

  • Hands-on experience with APIs for AI services like OpenAI, Cohere, or Google AI.

  • Familiarity with prompt engineering and fine-tuning Generative AI models.

  • Knowledge of MLOps practices for deploying and maintaining AI solutions.

  • Previous experience in automation or workflow optimization projects.

Benefits

Why Join Us?

  • Work with cutting-edge Generative AI technologies.

  • Collaborate with a team of forward-thinking innovators.

  • Make a tangible impact on the future of automation and AI-driven processes.

If you are passionate about leveraging Generative AI to create innovative automation solutions, we invite you to apply and be a part of our dynamic and growing team.

Apply