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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in Computational Biology, Bioinformatics, and Machine Learning, with a strong focus on integrating genomic and clinical data for innovative insights. Proficient in R and Python, with a solid understanding of cancer biology and the drug development lifecycle.
Highest-signal resume keywords
PhD In Computational BiologyProficiency In R And PythonMachine Learning ApplicationProject Leadership And MentorshipExperience Analyzing Large-Scale Biological Datasets
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
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Hard Skills
Computational BiologyBioinformaticsMachine LearningStatistical AnalysisData AnalysisCode ReviewQuality AssuranceSurvival AnalysisCausal InferenceNetwork Biology
Soft Skills
Excellent Communication SkillsMentorshipCollaboration
Tools & Technologies
Tempus Multimodal PlatformLLMsSQLVersion ControlScientific Computing Libraries
Industry Keywords
Clinical DevelopmentBiomarker DevelopmentDrug Development LifecycleReal-World EvidenceNGSRNA-seqTranscriptomics
Tech Stack
Tools & technologiesPythonSQL
About the role
Key responsibilities & impact- Partner with pharmaceutical collaborators on target discovery, biomarker development, and clinical development
- Translate partner needs into key questions, technical requirements, and analytical plans using the Tempus multimodal platform
- Execute reproducible analyses integrating genomic, transcriptomic, imaging, and clinical data
- Generate insights for clinical trial design, patient selection, treatment response, resistance mechanisms, and disease biology
- Incorporate LLMs and AI tools to automate and accelerate coding, discovery, documentation, and review
- Design and prototype agentic workflows using foundation models and LLMs for new insights and predictive models
- Evaluate, adapt, and implement methods for real-world, clinical, and omic datasets
- Contribute reusable code, internal packages, and analytical best practices
- Collaborate with Research, Clinical, Data Science, and Engineering teams on scalable solutions and platform/product roadmaps
- Communicate methods and results to technical and non-technical stakeholders
- Prepare internal reports, external deliverables, manuscripts, and conference materials
- Lead projects, set priorities, coordinate resources, address obstacles, mentor junior scientists, and ensure milestones are met
Requirements
What you’ll need- PhD in Computational Biology, Bioinformatics, Biostatistics, Machine Learning, or a related field, or a Master's degree with 4+ years of relevant experience
- Plus an additional 2+ years of relevant industry or post-doctoral experience
- Proven track record in peer-reviewed publications
- Proficiency in R and/or Python, including common computational biology and scientific computing libraries
- Proficiency applying machine learning, LLM-based coding assistants, and agentic frameworks for biological/clinical research
- Good software engineering practices, including version control, modular code, and documentation
- Strong grounding in statistics and data analysis, including study design and interpretation of real-world clinical data
- Proficiency in code review and QA/QC
- Strong understanding of cancer biology, immunology, or human disease mechanisms
- Experience analyzing large-scale biological datasets such as NGS, RNA-seq, genomics, or transcriptomics data
- Demonstrated project leadership and people mentorship
- Excellent written and verbal communication skills with comfort in client-facing roles
- Practical experience configuring or adapting LLMs or related tools/frameworks
- Expertise in RWE, survival analysis, causal inference, network/systems biology, or multi-modal integration
- Understanding of the drug development lifecycle
- Experience working with SQL and large relational databases
Benefits
Comp & perks- Incentive compensation
- Restricted stock units
- Medical benefits
- Other benefits depending on the position