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Remote Systematic Review Meta Analysis Jobs in Delaware

Lead the team to deploy and optimize ad campaigns across paid social platforms, including Meta ... Conduct performance reviews and work with direct reports on career development. * Maintain a deep ...

... and systematic manner. * Monitor, route, and assist with routine inquiries received by the Legal ... review of market conditions Flexible working hours and work arrangements Remote and hybrid ...

This is a flexible, remote opportunity ideal for veterinarians looking to pick up additional work ... reviewing applications, analyzing resumes, or assessing responses and identifying potential ...

This is a flexible, remote opportunity ideal for veterinarians looking to pick up additional work ... reviewing applications, analyzing resumes, or assessing responses and identifying potential ...

Monday-Friday, 8AM to 5PM (4 days in office, 1 day remote) About the Opportunity: The Investor ... Generate and review reports within your area of responsibility to ensure operational oversight and ...

Position Summary Under close supervision, the Junior Property Compliance Analyst will complete a ... review of market conditions * Flexible working hours and work arrangements * Remote and hybrid ...

Reviews and interprets Inpatient, Outpatient, Ancillary, Diagnostics and Emergency Medicine or ... Works with the HIMS Coding Systems Analyst under the direction of HIMS management to achieve the IT ...

Reviews and interprets Inpatient, Outpatient, Ancillary, Diagnostics and Emergency Medicine or ... Works with the HIMS Coding Systems Analyst under the direction of HIMS management to achieve the IT ...

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Remote Systematic Review Meta Analysis information

What is a remote systematic review meta analysis?

Remote Systematic Review Meta Analysis jobs involve conducting comprehensive reviews of existing research studies from a remote location, often to answer specific clinical or scientific questions. These roles typically require summarizing and synthesizing data from multiple studies, evaluating study quality, and performing statistical meta-analyses to identify overall trends and conclusions. Professionals in these positions often work for academic institutions, healthcare organizations, or research consultancies, using specialized software and databases to manage and analyze large volumes of scientific literature. Remote work enables flexibility and access to global projects, making these jobs attractive to researchers and analysts across various fields.

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

Working remotely on systematic reviews and meta-analyses often involves coordinating with team members across different time zones, ensuring consistent data management, and maintaining clear communication. Common challenges include version control of documents, discrepancies in data extraction, and delays in feedback cycles. These can be addressed by using collaborative tools (like shared databases and cloud platforms), establishing regular virtual meetings, and setting clear protocols for documentation and decision-making. Proactively addressing these challenges helps maintain accuracy, efficiency, and team cohesion throughout the review process.

What are the key skills and qualifications needed to thrive as a remote systematic review meta analysis specialist, and why are they important?

To excel in Remote Systematic Review Meta Analysis, a strong background in research methodology, statistical analysis, and evidence-based practices—often supported by advanced degrees in health sciences or related fields—is essential. Proficiency in software such as RevMan, EndNote, Covidence, and statistical tools like R or Stata, along with knowledge of PRISMA guidelines, is typically required. Exceptional attention to detail, critical thinking, and clear written communication are vital soft skills for synthesizing complex data and collaborating remotely. These competencies ensure the integrity, accuracy, and reliability of published systematic reviews and meta-analyses.

What is the difference between Remote Systematic Review Meta Analysis vs Remote Research Analyst?

AspectRemote Systematic Review Meta AnalysisRemote Research Analyst
CredentialsAdvanced degrees in health sciences, research methods, or related fieldsBachelor's or master's in research, statistics, or related areas
Work EnvironmentPrimarily academic, healthcare, or research institutions; focused on literature synthesisVaried settings including market research, healthcare, or academia; data collection and analysis
Industry UsageCommon in healthcare, academia, and policy-makingUsed across multiple industries including healthcare, marketing, and finance

Remote Systematic Review Meta Analysis specialists focus on synthesizing research data through systematic reviews and meta-analyses, requiring advanced research credentials. Remote Research Analysts perform broader data collection and analysis tasks across industries, often with less specialized qualifications. While both roles involve research skills, the systematic review meta analysis role is more specialized in evidence synthesis within healthcare and academia.

What are popular job titles related to Remote Systematic Review Meta Analysis jobs in Delaware?

For Remote Systematic Review Meta Analysis jobs in Delaware, the most frequently searched job titles are:

What job categories do people searching Remote Systematic Review Meta Analysis jobs in Delaware look for?

The top searched job categories for Remote Systematic Review Meta Analysis jobs in Delaware are:

What cities in Delaware are hiring for Remote Systematic Review Meta Analysis jobs?

Cities in Delaware with the most Remote Systematic Review Meta Analysis job openings:

Infographic showing various Remote Systematic Review Meta Analysis job openings in Delaware as of July 2026, with employment types broken down into 83% Full Time, 15% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution.

Senior Director of Data Science (Remote)

Forbes Advisor

Wilmington, DE • On-site, Remote

Full-time

Re-posted 19 days ago


Job description

At Forbes Advisor, our mission is to help readers turn their aspirations into reality. We arm people with trusted advice and guidance so they can make informed decisions they feel confident in and get back to doing the things they care about most.
We are an experienced team of industry experts dedicated to helping readers make smart decisions and choose the right products with ease. Forbes Advisor boasts decades of experience across dozens of geographies and teams, including Content, SEO, Business Intelligence, Finance, HR, Marketing, Production, Technology and Sales. The team brings rich industry knowledge to Forbes Advisor's global coverage of consumer credit, debt, health, home improvement, banking, investing, credit cards, small business, education, insurance, loans, real estate and travel.
Our Data & Analytics organisation builds the products, platforms and intelligence that power every marketing, product and commercial decision across the business. We're looking for a Data Science leader who believes machine learning only creates value when it changes business decisions.
This is an opportunity to build and lead a commercially driven Data Science function that delivers measurable improvements in customer acquisition, marketing performance and long-term business growth.
You'll lead a growing team of Data Scientists while partnering closely with Engineering, Analytics, Product and Commercial teams to ensure predictive models become trusted, production-ready products that drive measurable commercial outcomes. As we continue investing in first-party data, AI, machine learning and advanced marketing measurement, we're looking for an experienced Data Science leader to help shape the next phase of our commercial Data Science capability.
Responsibilties:
  • Commercial Data Science: Lead the strategy and delivery of predictive models that improve customer acquisition, marketing performance and long-term commercial value. You'll shape capabilities including lifetime value modelling, propensity modelling, customer segmentation, forecasting and value-based bidding, ensuring every model is linked to measurable business outcomes.
  • Marketing Science & Decision Science: Partner with Marketing, Product and Commercial teams to apply Data Science to real business problems. You'll help define how predictive analytics, experimentation and AI improve campaign performance, customer understanding and strategic decision making across platforms including Google and Meta.
  • Production Data Science: Work closely with Engineering and ML Ops to ensure models become reliable, production-ready products rather than one-off analyses. You'll champion reproducible experimentation, scalable deployment, model monitoring, retraining strategies and continuous improvement throughout the model lifecycle.
  • Leadership & Stakeholder Management: Lead and develop a growing team of Data Scientists while building trusted relationships across the business. You'll translate complex modelling into clear commercial recommendations, influence senior stakeholders through evidence, and help establish Data Science as a trusted driver of business strategy and commercial growth.
  • Innovation & Industry Leadership: Represent Forbes in strategic conversations with technology partners including Google and Meta while staying connected to advances in AI, machine learning and marketing science. You'll evaluate emerging technologies, bring new ideas into the organisation and help ensure our Data Science capability remains commercially relevant and technically leading.

Qualifications:
  • Experience leading commercial Data Science, Marketing Science or Decision Science teams.
  • Strong expertise in predictive analytics, customer analytics, machine learning and statistical modelling.
  • Experience applying Data Science to marketing performance, customer acquisition, lifetime value or value-based bidding.
  • Experience productionising machine learning solutions within modern cloud environments and working closely with Engineering and ML Ops teams.
  • Strong understanding of SQL, Python and modern machine learning frameworks.
  • Experience working with Google Ads, Meta or other major advertising platforms.
  • Excellent stakeholder management and communication skills, with the ability to influence both technical and commercial audiences.
  • Experience building and developing high-performing Data Science teams.
  • Strong commercial judgement, balancing technical excellence with measurable business impact.
  • A pragmatic approach to AI, applying emerging technologies where they create genuine commercial value.

Nice to Have
  • Experience within affiliate marketing, digital publishing or lead-generation businesses.
  • Experience working in financial services, insurance or regulated industries.
  • Experience working directly with Google or Meta Data Science teams.
  • Experience with attribution modelling and marketing measurement.
  • Experience building optimisation algorithms for DSPs or advertising platforms.
  • Experience with causal inference, experimentation frameworks or incrementality testing.
  • Experience forecasting marketing or commercial performance.
  • Experience with Vertex AI or equivalent cloud-based machine learning platforms.

Forbes Advisor provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
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