Data Analyst - Biomedical SaaS

at  Lumerate

Lumerate is growing rapidly, and we’re searching for a Data Analyst - Biomedical SaaS to join our team for the journey!

WHO IS LUMERATE?

Lumerate is a Toronto-based SaaS company that has built game-changing technology to help sales teams accelerate revenue growth. We help our customers achieve the full picture of their industries. We also strive to achieve our own personal full pictures from a career fulfillment and learning perspective. We’re in the business of gathering intelligence about industries and delivering it to the right people within those industries through innovative software interfaces. Our vision is to be the world’s most useful and trusted source of information for professionals seeking to understand what’s happening in their industry. Our mission is to deliver industry awareness to an ever-increasing number of people, in whatever way helps them to make the most informed decisions, take the most immediate action and be the most awesome at their unique jobs.
This Data Analyst - Biomedical SaaS role is ideal for a recent graduate or someone looking to kickstart their career in data analysis. You’ll be responsible for data cleaning and preprocessing to ensure the highest standards of data quality and accuracy.

CORE SKILLS AND EXPERIENCE

• Bachelors (required), Masters or PhD (preference) in a biomedical field of science
• You have conducted biomedical research during your career, meaning you’ve used a pipette outside of coursework (Note: While this role does not involve working in a wet lab, we are looking for someone who has hands-on lab experience)
• You are proficient with medium-complexity functions in Google Sheets or Excel
• You are meticulous and have a keen eye for detail
• You enjoy puzzles, which is why you will find and include the word located at these coordinates 43.63565745335677, -79.43972483985826 in your cover letter

• Hunting for information on the web and within hard-to-reach datasets
• Organizing and structuring unstructured data
• Setting up workflows in Google Sheets
• Working with LLMs (prompt engineering)
• Running experiments and documenting your findings
• Becoming proficient in various scripting languages
• Using industrial-scale AI tools to enhance and scale your research efforts
• Tracking changes within specific online data sources
• Working with commercial teams to align data efforts with customer priorities