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From Home Systematic Review Meta Analysis Jobs in Ohio

Meta

Lead Building Engineer

New Albany, OH · On-site

$104K/yr

Meta is seeking a Lead Building Engineer to join our Data Center Critical Facility Operations team ... Lead the development, review, and continuous improvement of standard operating procedures ...

The Jernigan Agency

WORK FROM HOME

Cincinnati, OH · On-site +1

$300 - $500/wk

We are looking for individuals interested in working from home, remotely, as life insurance sales ... Help each client to review their options and apply for that coverage. * See the application through ...

The Jernigan Agency

WORK FROM HOME

Dayton, OH · On-site +1

$300 - $500/wk

We are looking for individuals interested in working from home, remotely, as life insurance sales ... Help each client to review their options and apply for that coverage. * See the application through ...

Meta

Leased Facility Engineer

New Albany, OH

$104K/yr

The Leased Facility Engineer (LFE) is a key onsite role within Meta's Global Leased Facility ... Conduct incident review meetings for ongoing issues and open action items * Support training of new ...

Meta

Lead Building Engineer

Bowling Green, OH

$129K/yr

Meta is seeking a data center lead building engineer to join our data center facility operations ... Review all operating procedures, serve as the final approval authority on some procedures based on ...

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All JobsSystematic Review Meta Analysis JobsFrom Home Systematic Review Meta Analysis JobsFrom Home Systematic Review Meta Analysis Jobs in Ohio

From Home Systematic Review Meta Analysis information

What is a from home systematic review meta analysis job?

A work-from-home systematic review and meta-analysis job involves conducting comprehensive literature reviews and statistical analyses of existing research from a remote location. Professionals in this role systematically collect, evaluate, and synthesize data from multiple studies on a specific topic to draw evidence-based conclusions. The work often supports research projects in healthcare, social sciences, or other fields requiring high-quality evidence summaries. Remote workers use various online databases, analytical software, and collaboration tools to perform their duties efficiently from home.

What are some common challenges faced when conducting systematic reviews and meta-analyses from home, and how can they be addressed?

One of the main challenges of conducting systematic reviews and meta-analyses from home is maintaining effective collaboration with co-authors and ensuring consistent access to shared data and reference management tools. To address this, it's important to use secure, cloud-based platforms for document sharing and to schedule regular virtual meetings to discuss progress and resolve any issues. Additionally, managing distractions and maintaining motivation in a remote environment can be challenging; setting clear milestones and using task management tools can help stay on track. Staying updated with best practices and new tools in evidence synthesis is also crucial for producing high-quality reviews.

What are the key skills and qualifications needed to thrive as a systematic review and meta-analysis researcher working from home, and why are they important?

To thrive as a Systematic Review and Meta-Analysis Researcher, you need expertise in literature search strategies, critical appraisal, and advanced statistical analysis, typically supported by a degree in a health or social sciences field. Familiarity with databases like PubMed, systematic review management tools (e.g., Covidence), and statistical software (e.g., RevMan, Stata, R) is standard, and PRISMA or Cochrane training is advantageous. Strong attention to detail, time management, and effective written communication are crucial soft skills for remote collaboration and high-quality reporting. These skills ensure the accuracy, transparency, and reliability of research findings, which are essential for evidence-based decision-making.

What is the difference between From Home Systematic Review Meta Analysis vs From Home Research Assistant?

AspectFrom Home Systematic Review Meta AnalysisFrom Home Research Assistant
CredentialsTypically requires advanced degrees (Master's or PhD) in related fieldsOften requires a Bachelor's or Master's degree in a relevant discipline
Work EnvironmentPrimarily remote, focused on analyzing existing data and literatureRemote or office-based, involved in data collection, literature review, and support tasks
Industry UsageCommon in healthcare, social sciences, and academic researchUsed across various industries including healthcare, market research, and academia

From Home Systematic Review Meta Analysis involves synthesizing existing research to draw conclusions, requiring strong analytical skills. In contrast, From Home Research Assistants support research projects through data collection and literature review. Both roles are remote but differ in complexity and responsibilities.

What are the most commonly searched types of Systematic Review Meta Analysis jobs in Ohio?

The most popular types of Systematic Review Meta Analysis jobs in Ohio are:

What are popular job titles related to From Home Systematic Review Meta Analysis jobs in Ohio?

For From Home Systematic Review Meta Analysis jobs in Ohio, the most frequently searched job titles are:

What job categories do people searching From Home Systematic Review Meta Analysis jobs in Ohio look for?

The top searched job categories for From Home Systematic Review Meta Analysis jobs in Ohio are:

From Home Systematic Review Meta Analysis jobs near you
Infographic showing various From Home Systematic Review Meta Analysis job openings in Ohio as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, and 4% Contract. Highlights an 79% Physical, 1% Hybrid, and 20% Remote job distribution.

Scientist- Data Research and Development USA

First Solar

Perrysburg, OH • On-site

Full-time

Re-posted 14 days ago

First Solar rating

6.5

Company rating: 6.5 out of 10

Based on 76 frontline employees who took The Breakroom Quiz

477th of 545 rated manufacturers

Job description


First Solar reserves the right to offer you a role most applicable to your experience and skillset.
Basic Job Functions:
This position supports large scale statistical experiment design and analysis to evaluate innovative ideas on thin-film processes. You will join many disparate data sources to compile an integrated story of discovery, within and across experiments, projects, and people. You will apply an advanced knowledge of statistics and data science techniques to recognize patterns and create insights in a state-of-the-art R&D solar fabrication facility. Design, develop, and evaluate experimental models that point in the direction of maximum success. Serve as lead statistician for project teams, providing expertise, oversight, and guidance on analysis efforts. Provide support, training, and direction to all Advanced Research Engineers on DOE, statistical analysis, and modeling. Help your colleagues build a world and workplace that is just sustainable, and equitable.
Education/Experience:
  • Bachelor's Degree in Computer Science, Information Systems, Engineering, Data Science, or similar technical discipline, and 5 years of relevant technical experience or 2 years of experience as an Engineer- Analytics R&D at First Solar.
  • Master's Degree in Computer Science, Information Systems, Engineering, Data Science, or similar technical discipline, and 3 years of relevant technical experience or 2 years of experience as an Engineer- Analytics R&D at First Solar.
  • Ph.D. in Computer Science, Information Systems, Engineering, Data Science, or similar technical discipline, without prior technical work experience.
  • Previous R&D, PV, or Semiconductor experience helpful, but not necessary.

Required Skills/Competencies:
  • Deep understanding of Design of Experiments.
  • Meta-analysis and systematic research review.
  • Data forensics and partitioning on large data sets.
  • Data Wrangling: preparation, mapping, and transformation.
  • Structured and unstructured data sets.
  • Executive level storytelling with data visualization.
  • Impart clarity when communicating complex data relationships.
  • Linear Algebra: Matrix Algebra and eigenvalues/vectors.
  • Passion to learn new areas of study (device physics learning will be intensive).
  • High emotional intelligence.
  • Bravery to speak a dissenting opinion or present evidence against current belief.
  • Skilled in a structured problem-solving method (such as DMAIC, A3, 5 Whys, etc.).
  • Extensive understanding of Probability and Inferential Statistics as well as visual display of these concepts.
  • Expert at building predictive models and utilizing advanced statistical analysis, including generalized linear models, decision trees, PCA, logistic and multivariate regression.
  • Deep knowledge of statistical and modeling software tools and scripting languages such as JMP, SAS, Python, SPSS, or R to manipulate data and draw insights from large data sets.
  • Experience with Microsoft environment: Windows OS, Office 365, Teams, SharePoint, etc.

Essential Responsibilities:
  • Development Program Statistical Research & Meta-analysis (70%)
    • While assigned to a Development Program, serve as statistical expert and work with Technical, Operations and Process Engineering Teams to achieve program goals via research, modeling, experiment design and analysis.
    • Gain deep understanding of program objectives, learning the physics behind the processes to know current and predict future Program Team needs.
    • Help Team define an experiment's statement of intent, reviewing previous responses and assuring factor estimability is understood.
    • Systematic review of prior experimentation to find relevant, high-quality data, while accounting for variability in study approach, sample size, execution, environment, etc.
    • Standardize and weight prior research to build new predictive models to guide Program experimentation.
    • Understand experimenter's needs and develop custom experiment design to efficiently create insight.
    • Exhaustively evaluate experiment design and resulting model.
    • Work with Program Partners to define and prepare datasets for modeling.
    • Monitor many data streams and feedback data quality to Program Teams.
    • Be the data forensics Program Lead, data mining root cause of un-intended processing artifacts.
    • Explore data using a variety of statistical (e.g., data mining, regression, cluster analysis, partitioning, PCA) techniques to answer research questions and guide future experiments.
    • Synthesize independent experiment findings into overall treatment effects.
    • Prepare testing scenarios and test model performance against new results, subsets, etc.
    • Clearly and concisely communicate analysis and modeling results to business partners, supporting socialization and adoption of results into business activities and decisions.
    • Perform Program meta-analysis, putting the newest experiment in context with history, highlighting key abnormalities, consistencies, and correlations.

  • Data Science & Statistics Subject Matter Expert (30%)
    • Define data structures and systems that will institutionalize improvements and lower the bar for analysis across the organization.
    • Hone and proliferate the craft of cross-experiment meta-analysis in Research & Development.
    • Assist in development of standard analytical approaches and methodologies for the department.
    • Apply advanced statistical techniques, including analysis of variance, t-tests, factor analysis, regression, multivariate analyses, PCA or simulation, to analyze the effects of experimentation.
    • Provide guidance and direction related to statistical analysis to less experienced Research & Development staff as needed.
    • Provide peer review related to analytics methods and results.
    • Work closely with Development Technical Teams to identify and answer critical questions.
    • Identify and scope new opportunities for statistical analysis applications and scripting.
    • Proactively research and leverage new statistical techniques and technologies to apply and teach.
    • Develop and lead training sessions for advanced Data Science & Statistics concepts.
  • Other duties as assigned.
  • Job description subject to change at any time.

Reporting Relationships:
  • This position will report to the Analytics Manager.
  • This position may have direct reports.

Travel:
  • 0% - 5% (On occasion/as needed for training, etc.)

Estimated Salary Range:
  • $91,200-$130,000 Annually

US Physical Requirements:
  • Will sit, stand or walk short distances for up to the entire duration of a shift.
  • Will climb stairs on an occasional basis.
  • Will lift, push or pull up to 37 pounds on an occasional basis.
  • Required to use hands to grasp, lift, handle, carry or feel objects on a frequent basis.
  • 20/40 vision in both eyes together, with or without correction, is required.
  • Must be able to comply with all safety standards and procedures.
  • May reach above shoulder heights and below the waist on a frequent basis.
  • May stoop, kneel, or bend, on an occasional basis.
  • Ability to wear personal protective equipment is required (including but not limited to; steel-toed shoes, gloves, safety glasses, hearing protection, protective jacket or apron and arm guards, and a condition of employment and continued employment (requires little or no facial hair) for those requiring respirator use.

Potential candidates will meet the education and experience requirements provided on the above job description and excel in completing the listed responsibilities for this role. All candidates receiving an offer of employment must successfully complete a background check and any other tests that may be required.
Equal Opportunity Employer Statement: First Solar is an Equal Opportunity Employer that values and respects the importance of a diverse and inclusive workforce. It is the policy of the company to recruit, hire, train and promote persons in all job titles without regard to race, color, religion, sex, age, national origin, veteran status, disability, sexual orientation, or gender identity. We recognize that diversity and inclusion is a driving force in the success of our company.

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