Are you a motivated team player, with a combination of analytical, research, technical and communication skills? Would you like to join a dynamic health-tech company leveraging cutting-edge technology to deliver life-changing solutions that directly impact cancer and rare disease patients worldwide?
If this sounds like you and you are driven by purpose, join the SOPHiA GENETICS Biostatistics team in Pessac as our Healthcare Senior Data Scientist, and enable us to make a positive impact on the outcomes for cancer and rare disease patients worldwide.
Our mission
We believe there is a smarter, more data-driven way to make decisions in healthcare and our cloud-native AI powered SOPHiA DDM Platform makes that vision a reality on a daily basis. You will have direct input to our mission to democratize data-driven medicine for the ultimate benefit of cancer and rare disease patients across the globe.
Your mission
As our Healthcare Senior Data Scientist, you will help solve the problems faced by hospitals and biopharmaceutical partners in innovative and effective ways. You will carry out explanatory and predictive statistical studies using multimodal and longitudinal data. You will then present your results using clear and engaging language to make them understandable to a non-specialized public. You will also participate in the deployment of machine learning / deep learning models into production.
The value you bring
Carry out statistical studies to explain/predict clinical outcomes using multimodal data in patients treated for cancer
Use cutting-edge machine learning/deep learning methods to develop multimodal predictors intended for use by pharmaceutical companies and clinicians
Help the team to write statistical analysis plans and detailed analysis reports for stakeholders
Present your statistical results to a specialist or non-specialist audience (e.g., clinicians, data science team or IT team)
Participate in the team’s research activities to both improve our findings and suggest new areas for development
Work closely with medical and IT team to translate models and algorithms into engineered production applications