Senior Data Scientist

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This range is provided by Aditi Consulting. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

$70.50/hr - $80.59/hr

Payrate: $70.50 - $80.59/hr.

Summary:
The Computational Biology group in the Clinical Biomarkers & Diagnostics (CBD) department is seeking a highly motivated Sr data scientist to join our team and contribute to developing machine learning modeling and prediction pipelines using multi-modal biomarker data from clinical trials.

Responsibilities:

• Maintain and develop in-house endpoint association and modeling/prediction pipeline that use cutting edge machine learning methodologies to develop biomarkers of clinical response and resistance, extend analytical capabilities of biomarker platform
• Develop and maintain in-house survival prediction pipeline that use multi-omics data to predict survival endpoints
• Perform multi-omics integration analysis
• Perform pan-study analysis to find biomarkers that are predictive of safety and efficacy endpoints.
• Serve as a subject matter expert and implementation lead for application of open-source R and python ML modeling libraries to clinical trial data and real-world data (from external partners, publicly available data or consortia data).
• Work cross-functionally with stakeholders in Research and Development.
• Communicate findings and insights and present them to the team.

• PhD or MS in Bioinformatics, Mathematics, Statistics, Computer Science, or a related quantitative field.
• Significant experience in bioinformatics, applied mathematics and/or statistics to analyze multi-modal, multi-dimensional and large-scale biological datasets including whole genome/exome sequencing, RNA-seq, and high-throughput proteomics data.
• Familiarity of clinical bioinformatics domain and associated technologies, real world biomarker data
• Working experience of data QC, data preprocessing, feature selection, model building and deployment.
• Fluency in both Python and R programming languages and associated Dev Ops tools (version control, ML Ops).
• Ability to work in a highly matrixed environment and drive scientific and technical innovation collaboratively with other group members and with the research community.
• Strong written and oral communication skills, self-motivation, independence, and leadership.

• Maintain and develop in-house endpoint association and modeling/prediction pipeline that use cutting edge machine learning methodologies to develop biomarkers of clinical response and resistance, extend analytical capabilities of biomarker platform
• Develop and maintain in-house survival prediction pipeline that use multi-omics data to predict survival endpoints
• Perform multi-omics integration analysis
• Perform pan-study analysis to find biomarkers that are predictive of safety and efficacy endpoints.
• Serve as a subject matter expert and implementation lead for application of open-source R and python ML modeling libraries to clinical trial data and real-world data (from external partners, publicly available data or consortia data).
• Work cross-functionally with stakeholders in Research and Development.
• Communicate findings and insights and present them to the team.

• PhD or MS in Bioinformatics, Mathematics, Statistics, Computer Science, or a related quantitative field.
• Significant experience in bioinformatics, applied mathematics and/or statistics to analyze multi-modal, multi-dimensional and large-scale biological datasets including whole genome/exome sequencing, RNA-seq, and high-throughput proteomics data.
• Familiarity of clinical bioinformatics domain and associated technologies, real world biomarker data
• Working experience of data QC, data preprocessing, feature selection, model building and…