This is a remote role*
Adela’s mission is to develop innovative and accessible technologies that harness biology and change the way we diagnose and treat disease. Adela’s genome-wide methylation enrichment technology was originally developed by Chief Scientific Officer Dr. Daniel De Carvalho, PhD, at University Health Network’s Princess Margaret Cancer Centre. Adela is initially planning to develop the technology for use across the entire cancer continuum—for detection, diagnosis and management of disease.
We are seeking a highly motivated and experienced Principal or Fellow Data Scientist to provide technical leadership and to develop novel and innovative algorithms for converting the raw signal from Adela’s genome-wide methylome enrichment platform into biological and clinically actionable insights. This role will be critical in developing Adela's genome-wide methylome enrichment platform, and MRD and MCED products. The relatively flat organizational structure of an early start up will provide ample opportunities for this role to impact product strategy and the R&D roadmap. Access to thousands of biobanked and clinical samples will facilitate novel scientific insights that will no doubt lead to publications in high impact journals. The ideal candidate will have a strong background in signal processing, statistical modeling, NGS bioinformatics and machine learning with extensive experience in high-plex omics platform development.
Essential Functions / Key Responsibilities:
- Provide technical leadership around data science and assay research and development initiatives. Advise on statistical and ML approaches and assist in prioritizing research and development activities.
- Contribute to product and R&D strategy.
- Characterize assay performance and sources of variability and bias. Advice on approaches for data QC and visualization.
- Develop and implement algorithms for supporting Adela’s Cancer Management portfolio (MRD, response monitoring, phenotypic characterization, response prediction, etc).
- Analyze and interpret complex data sets to identify new methylome biomarkers.
- Collaborate with cross-functional teams including molecular biology, biochemistry, and software engineering to drive product development and performance improvements
- Stay up-to-date with the latest advancements in machine learning, statistical modeling, and bioinformatics
- Work in a collaborative environment with a focus on reproducible research, shared data, and analysis code source control and sharing.
- Communicate findings and results to internal stakeholders and external collaborators
- Mentor junior data scientists and contribute to building a strong data science team. Opportunity for people management if desired.
- Present findings and progress on a regular basis to both scientific and non-scientific audiences.
- PhD in data science, statistics, math, bioinformatics, computer science, or a related field with 10+ years of relevant industry experience
- Expertise in statistical modeling, bioinformatics and machine learning
- Experience with next-generation sequencing technologies and analysis of genomic data
- Strong programming skills in Python, R, or another scripting language
- Strong problem-solving skills and ability to work independently
- Excellent communication and collaboration skills
- Knowledge of cancer biology and molecular diagnostics is a plus