Revvity | About Us
Revvity is a developer and provider of end-to-end solutions designed to help scientists, researchers, and clinicians solve the world’s greatest health challenges. We pair the enthusiasm of an industry disruptor with the experience of a longtime leader. Our team of 11,000+ colleagues from around the globe are vital to our success and the reason we’re able to push boundaries in pursuit of better human health.
Find your future at Revvity.
Key responsibilities
- Act as a bridge between business and digital teams, collaborating with analysts, product managers, engineers, and stakeholders
- Deliver data-driven insights by combining statistical analysis, data manipulation, and business acumen
- Design and maintain dashboards and KPIs using Power BI
- Perform autonomous data analysis using SQL and Python
- Partner with data engineers to define scalable data models and automate data workflows
- Apply data science techniques and explore LLMs to enhance analytical capabilities
- Present findings to peers and leadership in a clear, actionable format
- Adhere to data governance and analytics best practices
- Support assigned projects with relevant data inputs
- Mentor junior analysts and contribute to team development
Required Qualifications
- Bachelor’s degree in Data Science, Computer Science, Statistics, or related field
- 5–7 years of experience in data analysis or business intelligence
- Proficiency in , BI Tools, Power BI, SQL, and Python
- Experience in dashboarding, metrics tracking, and performance monitoring
- Expertise in Statistical analysis and Machine Learning tools and techniques like Regression, SVM, Random Forest etc.
- Strong analytical, problem-solving, and communication skills
- Ability to work independently and in cross-functional teams
- Commitment to continuous learning and improvement
Desired Qualifications
- Experience with cloud platforms (e.g., Azure, AWS, GCP)
- Familiarity with machine learning libraries (e.g., pandas, scikit-learn)
- Exposure to LLMs and their practical application in data analysis
- Knowledge of data governance, compliance, and best practices
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