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Revolution Analytics Jobs (NOW HIRING)

Revolution Space

IT Support Analyst

Boston, MA · On-site

$60K - $100K/yr

Revolution Space is seeking a strong IT Support Analyst to join our growing IT team. This role is central to supporting rapid company growth in a highly secure, compliance-driven environment (CMMC ...

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Revolution Analytics information

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$64.5K

$125.3K

$179K

How much do revolution analytics jobs pay per year?

As of Jul 15, 2026, the average yearly pay for revolution analytics in the United States is $125,326.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,000.00 and $149,000.00 per year, depending on experience, location, and employer.

What is the difference between Revolution Analytics vs Data Scientist?

AspectRevolution AnalyticsData Scientist
Required CredentialsTypically requires a background in statistics, data analysis, or computer science; familiarity with R and analytics toolsRequires degrees in statistics, computer science, or related fields; proficiency in programming languages like Python, R, and SQL
Work EnvironmentPrimarily in analytics or data-focused teams within organizations, often in tech, finance, or healthcare sectorsIn diverse industries including tech, finance, healthcare, and consulting; often in collaborative, research-driven settings
Employer & Industry UsageUsed by companies implementing advanced analytics and data modeling, especially those utilizing Revolution Analytics softwareEmployed across industries for data analysis, predictive modeling, and machine learning projects

Revolution Analytics professionals focus on deploying analytics solutions using specific software tools, while Data Scientists have broader roles involving data exploration, modeling, and insights across various platforms. Both roles require strong analytical skills, but Data Scientists often have a wider scope in data manipulation and machine learning.

What is Revolution Analytics?

Revolution Analytics is a company that specialized in providing software, services, and support for the R programming language, which is widely used for statistical computing and data analysis. Founded in 2007, Revolution Analytics developed 'Revolution R', an enhanced distribution of R designed for enterprise use, including features for big data and advanced analytics. In 2015, Microsoft acquired Revolution Analytics, and its technology has since been integrated into Microsoft’s data platforms, such as Microsoft R Server (now Microsoft Machine Learning Server). Revolution Analytics played a significant role in popularizing R for business and large-scale analytics.

How does a professional at Revolution Analytics typically collaborate with data scientists and IT teams to implement analytical solutions?

At Revolution Analytics, professionals often work closely with data scientists to understand analytical objectives and select appropriate statistical methods using R. Collaboration with IT teams is also key, as they help integrate these solutions into existing systems and ensure they are scalable and secure. Regular meetings, shared documentation, and cross-functional project teams are common practices to facilitate smooth communication and project delivery. This collaborative environment ensures that analytical solutions are both robust and aligned with organizational goals.

What are the key skills and qualifications needed to thrive as a Data Analyst using Revolution Analytics software, and why are they important?

To thrive as a Data Analyst using Revolution Analytics, you need a solid background in statistics, data analysis, and programming (especially in R), often supported by a degree in a quantitative field. Familiarity with Revolution R Enterprise, distributed computing platforms, and related data visualization or ETL tools is typically required. Strong problem-solving abilities, attention to detail, and effective communication set top performers apart in this role. These skills are crucial for extracting actionable insights from large datasets and conveying findings to stakeholders for data-driven decision-making.
More about Revolution Analytics jobs
What are the most commonly searched types of Revolution Analytics jobs? The most popular types of Revolution Analytics jobs are:
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Revolution Analytics jobs near you
Infographic showing various Revolution Analytics job openings in the United States as of July 2026, with employment types broken down into 1% Internship, 94% Full Time, 3% Part Time, and 2% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $125,326 per year, or $60.3 per hour.
Director, US Analytics, Lung

Director, US Analytics, Lung

Revolution Medicines

Redwood City, CA • Hybrid

Other

Posted 13 days ago

Job description

The Opportunity:

Reporting to the Executive Director, Lung Analytics & Insights, the Director, Lung Analytics will serve as the analytics lead for Revolution Medicines' lung cancer portfolio.

This role will partner closely with Commercial, Medical Affairs, Market Access, Clinical Development, and Business Operations to generate actionable insights that inform portfolio strategy, launch readiness, commercialization planning, and business performance.

The role requires a strong understanding of the lung cancer treatment landscape, patient journey, biomarker-driven markets, and oncology data assets.

This position is based at our Redwood City, CA headquarters, with flexibility for remote candidates willing to travel regularly to the office.

Responsibilities include:

  • Lead analytics strategy and execution for Revolution Medicines' lung cancer portfolio.

  • Partner with cross-functional stakeholders to identify key business questions and translate them into analytical plans and actionable recommendations.

  • Generate insights from patient-, physician-, claims-, EMR-, and market-level data to inform portfolio strategy, launch planning, and commercial decision-making.

  • Develop analyses to understand patient identification, biomarker testing patterns, treatment sequencing, referral pathways, and barriers to adoption.

  • Conduct market opportunity assessments, patient journey analyses, and competitive landscape evaluations to support strategic planning.

  • Design and execute segmentation, targeting, and opportunity identification analyses to inform customer engagement strategies.

  • Monitor evolving standards of care, treatment dynamics, and competitor activity across lung cancer indications.

  • Partner with Forecasting, Market Research, and Competitive Intelligence colleagues to develop an integrated view of market performance and future growth opportunities.

  • Lead development of key performance metrics, dashboards, and launch readiness assessments.

  • Inform data acquisition and data strategy decisions to ensure availability of fit-for-purpose oncology data assets.

  • Manage external analytics vendors and ensure timely delivery of high-quality analyses.

  • Communicate insights and strategic implications to senior leadership through clear, concise, and compelling recommendations.

  • Represent Revolution Medicines' values in all internal and external interactions.

Required Skills, Experience and Education

  • Bachelor's degree required; advanced degree preferred.

  • 8+ years of experience in pharmaceutical, biotechnology, healthcare analytics, or management consulting.

  • Oncology analytics experience required; lung cancer experience strongly preferred.

  • Demonstrated expertise working with healthcare claims, EMR, specialty pharmacy, and other patient-level datasets.

  • Experience supporting oncology product launches and pre-launch planning.

  • Strong analytical, problem-solving, and strategic thinking skills.

  • Proven ability to influence cross-functional teams and senior leadership.

  • Excellent communication and presentation skills.

  • Ability to thrive in a fast-paced, entrepreneurial environment.

Preferred Skills:

  • MBA, MPH, MS, or PhD.

  • Deep understanding of NSCLC and biomarker-driven oncology markets.

  • Experience supporting targeted oncology therapies.

  • Experience with advanced analytics, predictive modeling, AI/ML applications, or commercial forecasting.

  • Prior experience in a growth-stage biotechnology company.

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