Sr Data Scientist

Dale WorkForce Solutions; South San Francisco (CA); Remote; USD 120,000 - 200,000; Full time

Job summary

A leading company in the biotech sector is seeking a passionate Senior Data Scientist to contribute to the development of machine learning models and pipelines using multi-modal biomarker data from clinical trials. This role involves performing analysis to predict survival endpoints and collaborating across functions within the organization. The ideal candidate should have a strong background in bioinformatics or related fields and be proficient in both Python and R programming languages.

Qualifications

• Doctorate with 1-2 years, Master’s with 3-5 years, or Bachelor’s with 5-7 years of experience.
• Significant experience in analyzing biological datasets.
• Fluency in Python and R programming languages.

Responsibilities

• Develop in-house endpoint association and modeling/prediction pipelines.
• Perform multi-omics integration analysis.
• Work cross-functionally with stakeholders.

Skills

Machine learning

Bioinformatics

Data analysis

Python

R

Communication

Education

Doctorate degree

Master’s degree

Bachelor’s degree

Tools

R programming

Python programming

Job description

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Client: Biotech

Position: Senior Data Scientist, Computational Biology

Location: Remote (PST hours)

Duration: 6 month contract with extensions (up to 3 years total)

The Computational Biology group in the Clinical Biomarkers & Diagnostics (CBD) department at Client is seeking a highly motivated Sr data scientist to join our team and contribute to develop 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.
  
  

Basic Qualifications

Doctorate degree and 1-2 years of scientific experience

OR

Master’s degree and 3-5 years of scientific experience

OR

Bachelor’s degree and 5-7 years of scientific experience

Preferred Qualifications

• 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 DevOps 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 Client research community.
• Strong written and oral communication skills, self-motivation, independence, and leadership.

Seniority level

• Seniority level

  Entry level

Employment type

• Employment type

  Contract

Job function

• Job function

  Information Technology

• Industries

  Pharmaceutical Manufacturing

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