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Remote Data Analysis Jobs in Springfield, MO (NOW HIRING)

Remote micro1 is engaging Biostatisticians to contribute their clinical statistics expertise to a ... missing data handling in alignment with the statistical analysis plan (SAP). * Identify ...

... remote workers nationwide. With seven interconnected EMR platforms feeding data into UKG, our ... Demonstrated ability to analyze data, troubleshoot issues, enforce accuracy, and lead a ...

Biostatistician

Springfield, MO · Remote

$60 - $100/hr

Remote micro1 is engaging Biostatisticians to contribute to a customer's advanced project in AI ... Source, construct, and curate authentic datasets including trial data, patient records, and ...

Remote We are seeking seasoned Funds Attorneys for a part-time role at the forefront of legal AI ... Collaborate with product and research teams to refine data, guidelines, and best practices for AI ...

Remote micro1 is engaging Biostatisticians to contribute to a customer's advanced project in AI ... Source, construct, and curate authentic datasets including trial data, patient records, and ...

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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 Springfield, MO?

The most popular types of Data Analysis jobs in Springfield, MO are:

What are popular job titles related to Remote Data Analysis jobs in Springfield, MO?

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

What job categories do people searching Remote Data Analysis jobs in Springfield, MO look for?

The top searched job categories for Remote Data Analysis jobs in Springfield, MO are:

What cities near Springfield, MO are hiring for Remote Data Analysis jobs?

Cities near Springfield, MO with the most Remote Data Analysis job openings:

Infographic showing various Remote Data Analysis job openings in Springfield, MO as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.

Director of Biostatistics

micro1 AI

Springfield, MO • Remote

$60 - $65/hr

Part-time

Re-posted 2 days ago


Job description

Role Title: Biostatistician


Role Type: Contractor


Location: Remote


micro1 is engaging Biostatisticians to contribute their clinical statistics expertise to a dynamic customer project focused on AI-assisted clinical research. 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. Author and review evaluation tasks that require deriving, reproducing, or validating statistical outputs from clinical datasets and associated tables, figures, and listings (TFLs).
  2. Apply expert judgment to assess the correctness and consistency of reported estimates, confidence intervals, p-values, analysis populations, and missing data handling in alignment with the statistical analysis plan (SAP).
  3. Identify discrepancies between statistical outputs and their narrative descriptions in clinical study reports (CSR), including subtle errors in population definitions, censoring rules, or multiplicity handling.
  4. Establish defensible ground truth for each evaluation task, documenting the derivation process to enable independent verification.
  5. Provide structured written rationales distinguishing true statistical errors from acceptable methodological alternatives, employing clear and concise communication.
  6. Collaborate with a multidisciplinary project team, providing statistical insights and feedback as needed to refine evaluation tasks and criteria.


Preferred Qualifications

  1. 5+ years as a biostatistician supporting clinical trials at a sponsor, CRO, or academic trials unit.
  2. Hands-on experience producing or quality controlling TFLs for regulatory submissions and working directly from CDISC SDTM/ADaM datasets.
  3. Solid understanding of statistical methods used in confirmatory trials, including survival analysis, mixed models, covariate adjustment, multiplicity control, and estimand and missing-data strategies under ICH E9(R1).
  4. Proficiency in SAS and/or R, with the ability to independently reproduce analyses from written specifications.
  5. Ability to interpret SAPs and ensure reported results are consistent with pre-specified analyses.
  6. Advanced degree (MSc or PhD) in Biostatistics, Statistics, or a closely related quantitative field.
  7. Nice to have: Experience as lead statistician on pivotal/registrational studies, authoring or reviewing CSR statistical sections, oncology endpoint expertise, and exposure to AI-assisted statistical review tools.