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Data Scientist R Remote Jobs in Michigan (NOW HIRING)

Must have a PhD in Engineering, Computer Science, Data Science, Physical Sciences, Business ... Remote work on Fridays may be permitted based on project priorities and business requirements ...

Senior Staff Data Engineer

Portage, MI · On-site +1

$153K - $255K/yr

Remote Join a team focused on building scalable, enterprise-grade data platforms that support ... Bachelor's degree in Computer Science, Data Analytics, Mathematics, Statistics, Data Science, or a ...

Showing results 41-60

Data Scientist R Remote information

What is a data scientist R remote?

Data Scientist R Remote jobs are positions where professionals use the R programming language to analyze and interpret complex data, develop statistical models, and generate actionable insights, all while working outside of a traditional office setting. These roles often involve collaborating with teams virtually, cleaning and preparing data, and building predictive models using R and related tools. Remote data scientists leverage cloud-based platforms and communication tools to work effectively from any location. The role typically requires strong analytical skills, proficiency in R, and experience with data visualization and machine learning techniques.

What are the key skills and qualifications needed to thrive as a data scientist R remote?

To thrive as a Data Scientist (R, Remote), you need strong analytical skills, statistical knowledge, and a background in mathematics or computer science, often supported by a relevant degree. Proficiency in R programming, data visualization tools, and familiarity with machine learning libraries are typically required, and certifications like the Microsoft Certified: Azure Data Scientist Associate can be advantageous. Excellent problem-solving abilities, effective communication, and self-motivation are critical soft skills for collaborating remotely and translating data insights into actionable business decisions. These skills enable you to derive meaningful insights from complex data sets, drive data-driven strategies, and work efficiently in a remote team environment.

How does a remote data scientist specializing in R typically collaborate with cross-functional teams?

As a remote Data Scientist with expertise in R, collaboration with cross-functional teams—such as product managers, engineers, and business analysts—is commonly facilitated through virtual meetings, shared documentation, and version control systems like Git. You'll often participate in sprint planning, present data-driven insights, and contribute to collaborative code reviews. Effective communication and proactive sharing of progress or challenges are key to ensuring alignment, especially when working across time zones. Utilizing tools like Slack, Jira, and cloud-based notebooks further streamlines teamwork and maintains project momentum.

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

AspectData Scientist R RemoteData Analyst R Remote
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related field; proficiency in RBachelor's in Statistics, Mathematics, or related field; proficiency in R
Work EnvironmentRemote, collaborative teams, project-basedRemote, reporting to managers, data reporting tasks
Employer & Industry UsageTech, finance, healthcare, consultingRetail, marketing, finance, healthcare
Common Search & ComparisonYesYes

Data Scientist R Remote and Data Analyst R Remote roles share similar skills in R programming and remote work environments. However, Data Scientists typically handle complex modeling, machine learning, and predictive analytics, requiring advanced statistical knowledge. Data Analysts focus on data reporting, visualization, and descriptive analysis. Both roles are vital across industries, but Data Scientists often require higher-level credentials and experience.

What cities in Michigan are hiring for Data Scientist R Remote jobs?

Cities in Michigan with the most Data Scientist R Remote job openings:

Bioinformatics Research Scientist - AI Reviewer

micro1 AI

Ann Arbor, MI • Remote

$80 - $110/hr

Part-time

Posted 16 days ago


Job description

Role Title: Computational Biology & Cheminformatics Expert


Role Type: Contractor


Location: Remote


micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their expertise to a customer’s computational drug discovery 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 — your domain knowledge is what matters.


Scope of Work

  1. Analyze and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods.
  2. Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank) to support AI-driven discovery platforms.
  3. Evaluate compound-target interactions, ADMET properties, and lead optimization strategies by integrating chemical, biological, and clinical data sources.
  4. Provide expert insights on structure-activity and structure-property relationships (SAR/SPR), medicinal chemistry approaches, and experimental design considerations.
  5. Build and implement code-based benchmark tasks (e.g., terminal/CLI-based environments) that reflect realistic computational drug discovery scenarios.
  6. Develop reproducible environments (e.g., using Docker) and automated testing pipelines to ensure task correctness and solvability.
  7. Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance, delivering detailed written feedback and recommendations.


Preferred Qualifications

  1. Advanced expertise in Computational Biology, Cheminformatics, Medicinal Chemistry, Biochemistry, or related fields; advanced degree (PhD, MSc, PharmD) highly valued but not strictly required.
  2. Strong coding proficiency in Python (beyond analysis scripts), with hands-on experience building tools, pipelines, or testable code; familiarity with Git, GitHub, and Docker.
  3. Extensive experience with cheminformatics toolkits and platforms such as RDKit, KNIME, Schrödinger, OpenEye, or MOE.
  4. Proven track record in small-molecule drug discovery, SAR/QSAR evaluation, ADMET prediction, or virtual screening workflows.
  5. Comfort working with public chemical and bioactivity databases and integrating diverse datasets for scientific analysis.
  6. Demonstrated ability to clearly communicate complex chemical and biological concepts in written feedback and reports.
  7. Experience participating in multidisciplinary and/or remote projects; familiarity with AI-assisted coding tools is a plus.