2

Remote Data Analysis Jobs in Mississippi (NOW HIRING)

Collaborate with product and research teams to refine data, guidelines, and best practices for AI ... Strong analytical capabilities and ability to translate legal expertise into actionable feedback ...

Collaborate with product and research teams to refine data, guidelines, and best practices for AI ... Strong analytical capabilities and ability to translate legal expertise into actionable feedback ...

Collaborate with product and research teams to refine data, guidelines, and best practices for AI ... Strong analytical capabilities and ability to translate legal expertise into actionable feedback ...

Collaborate with product and research teams to refine data, guidelines, and best practices for AI ... Strong analytical capabilities and ability to translate legal expertise into actionable feedback ...

Collaborate with product and research teams to refine data, guidelines, and best practices for AI ... Strong analytical capabilities and ability to translate legal expertise into actionable feedback ...

Showing results 21-40

Remote Data Analysis information

What is remote data analysis?

Remote data analysis refers to the process of examining, interpreting, and drawing insights from data using digital tools, while working from a location outside of a traditional office setting. Professionals in this field utilize statistical software, databases, and visualization tools to analyze large datasets and help organizations make informed decisions. Remote data analysts often collaborate with team members and stakeholders virtually, ensuring that data-driven strategies are implemented effectively. This role requires strong analytical skills, attention to detail, and the ability to communicate findings clearly.

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

To thrive as a Remote Data Analyst, you need strong analytical skills, statistical knowledge, and a background in fields like mathematics, statistics, or computer science. Proficiency with data analysis tools such as SQL, Python, R, and visualization platforms like Tableau or Power BI is typically required. Excellent communication, self-motivation, and time management help remote analysts present insights clearly and stay productive without direct supervision. These skills and qualities ensure accurate data-driven decisions and effective remote collaboration with stakeholders.

How do remote data analysts typically collaborate with team members and stakeholders?

Remote data analysts often use a combination of communication and project management tools—such as Slack, Microsoft Teams, and Zoom—to stay connected with colleagues and stakeholders. Regular virtual meetings, shared dashboards, and collaborative platforms enable them to discuss findings, gather requirements, and provide updates on ongoing projects. Clear documentation and proactive communication are essential to ensure alignment, especially when working across different time zones or departments. Building strong relationships with team members virtually can help streamline workflows and facilitate effective decision-making.

What is the difference between Remote Data Analysis vs Remote Data Entry?

AspectRemote Data AnalysisRemote Data Entry
Required SkillsData interpretation, statistical tools, analytical skillsTyping speed, accuracy, basic computer skills
Tools UsedExcel, SQL, data visualization softwareSpreadsheets, data entry platforms
Work EnvironmentAnalytical tasks, report creation, data insightsData input, database updating, record management
Common CertificationsData analysis certifications, Excel proficiencyNone typically required

Remote Data Analysis involves interpreting data, creating reports, and providing insights using analytical tools, while Remote Data Entry focuses on inputting and managing data accurately. Both roles are performed remotely and require computer skills, but Data Analysis demands analytical expertise and familiarity with data tools, whereas Data Entry emphasizes speed and accuracy in data input tasks.

Can I get a remote job as a remote data analyst?

Remote data analyst positions are widely available and often require skills in data visualization, statistical analysis, and proficiency with tools like Excel, SQL, or Python. Many companies offer remote roles with flexible schedules, and a strong portfolio or certification can improve job prospects.

Is data analysis a good career for remote work?

Data analysis is well-suited for remote work because it primarily involves computer-based tasks such as working with datasets, using tools like Excel, SQL, and Python, and communicating insights through reports. Many companies offer remote data analyst positions, and strong skills in data visualization and self-management are important for success in a remote environment.

What are the most commonly searched types of Data Analysis jobs in Mississippi?

The most popular types of Data Analysis jobs in Mississippi are:

What are popular job titles related to Remote Data Analysis jobs in Mississippi?

For Remote Data Analysis jobs in Mississippi, the most frequently searched job titles are:

What job categories do people searching Remote Data Analysis jobs in Mississippi look for?

The top searched job categories for Remote Data Analysis jobs in Mississippi are:

What cities in Mississippi are hiring for Remote Data Analysis jobs?

Cities in Mississippi with the most Remote Data Analysis job openings:

Infographic showing various Remote Data Analysis job openings in Mississippi as of August 2026, with employment types broken down into 94% Full Time, and 6% Part Time. Highlights an 6% In-person, and 94% Remote job distribution.

Cheminformatics Specialist - Remote

micro1 AI

Jackson, MS • Remote

$80 - $110/hr

Part-time

This job post has expired today. Applications are no longer accepted.


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.