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Remote Data Analyst R Programming Jobs in Alaska

... R tracking; support CPIR and asset verification; prepare technical documentation; ensure data ... Mid-level engineer or analyst experienced in utilities, GIS, or energy systems management.

Perform advanced engineering, economic, and regulatory analyses; review ACURRP, FCU, and R&R ... data analytic tools, and Visio, and the ability to quickly learn other tools, as necessary.

... Python or R for data manipulation and visualization is a plus * Strong problem solving and ... analytical skills resulting in pragmatic business solutions * Strong work ethics and preference for ...

Data Analysis: * Collect and analyze data to gain insights into user behaviour, product usage, and marketing performance. * Use data-driven decisions to guide growth strategies and experiments. Viral ...

Data Analysis: * Collect and analyze data to gain insights into user behaviour, product usage, and marketing performance. * Use data-driven decisions to guide growth strategies and experiments. Viral ...

Data Analysis: * Collect and analyze data to gain insights into user behaviour, product usage, and marketing performance. * Use data-driven decisions to guide growth strategies and experiments. Viral ...

Remote Position, preferably located in Alaska *Position is subject to contract award POSITION ... Evaluate biological, ecological, and regulatory data to determine project effects * Apply relevant ...

Analyze and annotate complex biological data sets, focusing on applications relevant to medicinal chemistry. * Provide feedback and domain-specific insights to improve AI models in computational ...

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Remote Data Analyst R Programming information

Do data analysts use R programming?

Data analysts often use R programming as it provides powerful tools for data manipulation, statistical analysis, and visualization. R is widely adopted in the field due to its extensive package ecosystem and open-source nature, making it a valuable skill for data analysis roles.

What are the key skills and qualifications needed to thrive as a remote data analyst specializing in R programming?

To thrive as a Remote Data Analyst specializing in R Programming, you need strong statistical analysis skills, proficiency in R, and a background in mathematics, statistics, or a related field. Experience with data visualization tools, databases (such as SQL), and familiarity with data science platforms or certifications like the Data Science Professional Certificate are commonly required. Effective communication, problem-solving abilities, and self-motivation are crucial soft skills for excelling in remote and collaborative environments. These skills ensure accurate data-driven insights, efficient workflow, and successful teamwork across distributed teams.

How does a remote data analyst specializing in r programming typically collaborate with team members across different locations?

As a Remote Data Analyst focused on R Programming, collaboration is often facilitated through digital communication tools such as Slack, Zoom, and project management platforms like Jira or Trello. Analysts regularly share scripts, data visualizations, and reports using version control systems like Git, ensuring code transparency and reproducibility. Team meetings and code reviews are scheduled to align on project goals, troubleshoot challenges, and maintain data integrity. Building strong communication skills and documenting code thoroughly are essential for effective teamwork in a remote environment.

What is the difference between Remote Data Analyst R Programming vs Remote Data Analyst Python?

AspectRemote Data Analyst R ProgrammingRemote Data Analyst Python
Required SkillsProficiency in R, data visualization, statistical analysisProficiency in Python, data manipulation, machine learning
Work EnvironmentRemote, data-focused roles in research, healthcare, financeRemote, data-driven roles in tech, e-commerce, finance
Common CertificationsR certifications, data analysis coursesPython certifications, data science courses

Both roles involve remote data analysis but differ mainly in programming language expertise. R-focused analysts excel in statistical analysis and visualization, often in research or healthcare sectors. Python analysts are versatile in data manipulation and machine learning, commonly working in tech or e-commerce. Understanding these differences helps job seekers target roles aligned with their skills and industry preferences.

What is a remote data analyst r programming?

A Remote Data Analyst R Programming is a professional who analyzes and interprets data using the R programming language while working from a remote location. Their primary responsibilities include collecting, cleaning, and visualizing data, as well as performing statistical analyses to help organizations make data-driven decisions. These analysts often collaborate with teams online and use R to automate processes, generate reports, and create predictive models. Remote work allows them flexibility and access to a wider range of employers, while R provides powerful tools for handling complex data tasks.

Are remote data analysts in demand?

Remote data analysts, including those skilled in R programming, are in high demand due to the increasing reliance on data-driven decision making across industries. Companies seek professionals with strong analytical skills, proficiency in tools like R and SQL, and the ability to work independently in virtual environments, leading to a growing job market for remote roles.
What are the most commonly searched types of Data Analyst R Programming jobs in Alaska? The most popular types of Data Analyst R Programming jobs in Alaska are:
What are popular job titles related to Remote Data Analyst R Programming jobs in Alaska? For Remote Data Analyst R Programming jobs in Alaska, the most frequently searched job titles are:
What job categories do people searching Remote Data Analyst R Programming jobs in Alaska look for? The top searched job categories for Remote Data Analyst R Programming jobs in Alaska are:
What cities in Alaska are hiring for Remote Data Analyst R Programming jobs? Cities in Alaska with the most Remote Data Analyst R Programming job openings:
Infographic showing various Remote Data Analyst R Programming job openings in Alaska as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Digital Chemistry Specialist - Remote

micro1 AI

Anchorage, AK โ€ข Remote

$90 - $120/hr

Part-time

Posted 10 days ago


Job description

Role Title: Bioinformatics Scientist


Role Type: Contractor


Location: Remote


micro1 is engaging Bioinformatics Scientists to contribute their specialized expertise to a customer's innovative project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required โ€” your domain knowledge is what matters.


Scope of Work

  1. Analyze complex datasets related to medicinal chemistry using advanced bioinformatics methodologies.
  2. Provide detailed scientific input and content to support the development and training of AI models.
  3. Curate, annotate, and validate datasets relevant to drug discovery and molecular analysis.
  4. Evaluate and synthesize findings from biological, chemical, and clinical data sources.
  5. Offer subject matter expertise on experimental design and data interpretation within medicinal chemistry.
  6. Assess AI-generated outputs for scientific accuracy, relevance, and reliability.
  7. Deliver comprehensive written feedback and actionable recommendations for model improvement.


Preferred Qualifications

  1. Advanced degree (e.g., PhD or MSc) in Bioinformatics, Computational Biology, Medicinal Chemistry, or a related discipline.
  2. In-depth knowledge of medicinal chemistry concepts, including structure-activity relationships and drug design principles.
  3. Demonstrated experience in handling and interpreting large-scale omics or cheminformatics datasets.
  4. Familiarity with software tools, databases, and programming languages commonly used in bioinformatics (e.g., Python, R, RDKit, KNIME).
  5. Strong scientific communication skills, with the ability to clearly articulate complex ideas and technical concepts.
  6. Proven track record of contributing to research projects at the intersection of biology, chemistry, and data science.
  7. Experience collaborating in multidisciplinary or remote project environments is advantageous.