Lead Bioinformatics Analyst

Jobtailor; City of Rochester (NY); On-site; USD 120,000 - 180,000; Full time

Job summary

Jobtailor seeks a senior bioinformatics lead to drive multi-omic data analyses for cancer research. You will oversee genomic, transcriptomic, and proteomic studies, guide methodological development, and collaborate with clinicians and researchers to translate findings into actionable insights.

The role requires strong leadership, program management, and effective communication to align resources with strategic research priorities.

Qualifications

• PhD with 3+ years in cancer research or related field.
• Strong data mining algorithms and ML knowledge.
• Familiarity with next generation sequencing analysis workflows.
• Proficiency in R and Python.
• Excellent communication skills.

Responsibilities

• Lead analysis of high-throughput multi-omic data to investigate tumor evolution and therapeutic resistance.
• Integrate clinico-genomic and spatial-omics modalities using machine learning and custom statistical methods.
• Provide scientific and programmatic leadership, including establishing program structure, priorities, capabilities, technologies, and processes.
• Develop educational materials for highly technical cancer biology research.
• Lead genomic, transcriptomic, and proteomic analyses to identify biomarkers and patient-specific insights.
• Lead strategic collaborations across multidisciplinary teams and serve as a scientific and programmatic liaison.
• Manage personnel, research and office space, computational infrastructure, software, equipment, supplies, and technical resources.

Skills

Data mining

Machine learning

R

Python

Communication

Education

PhD in relevant field

3+ years experience in cancer research or related field

Tools

R

Python

Job description

• Lead analysis of high-throughput multi-omic data to investigate tumor evolution, therapeutic resistance, and radiation-related phenotypes
• Integrate clinico-genomic and spatial-omics modalities using machine learning and custom statistical methods
• Direct bioinformatics operations and advise on complex oncological datasets
• Develop educational materials for highly technical cancer biology research
• Lead genomic, transcriptomic, and proteomic analyses to identify biomarkers and patient-specific insights
• Develop and integrate multi-modal omic datasets for computational modeling and translational research
• Collaborate with faculty, clinicians, bioinformaticians, and research partners nationally and internationally
• Provide scientific and programmatic leadership, including establishing program structure, priorities, capabilities, technologies, and processes
• Define and oversee program goals, resources, milestones, deliverables, and services
• Conduct complex analyses, develop recommendations, and present program outcomes and strategic priorities
• Lead development and implementation of data-driven research initiatives and computational strategies
• Recommend and implement analytical methodologies, infrastructure, software platforms, and technology investments
• Establish program standards, governance, workflows, change-management policies, and technical documentation
• Lead strategic collaborations across multidisciplinary teams and serve as a scientific and programmatic liaison
• Manage personnel, research and office space, computational infrastructure, software, equipment, supplies, and technical resources
• Participate in recruitment, hiring, onboarding, training, supervision, mentorship, performance management, and professional development of staff
• Lead and oversee internship and trainee programs
• Perform other duties as assigned

Requirements

• PhD and 3 years relevant experience required
• Or equivalent combination of education and experience
• Strong knowledge of data mining algorithms, including machine learning techniques required
• Scientific insight and statistics background in the field of cancer research, biology, and bioinformatics required
• Familiarity with next generation sequencing analysis workflows required
• Strong proficiency with one or more programming languages, such as R and Python required
• Excellent communication, interpersonal, verbal, presentation and written skills required

Core Competencies

Demonstrates expertise in leading multi-omic data analysis, integrating clinico-genomic and spatial-omics modalities, and applying machine learning techniques in cancer research. Proven ability to provide scientific leadership, manage multidisciplinary teams, and develop educational materials in a complex research environment.

Highest-signal resume keywords

• PhD In Relevant Field
• Data Mining Algorithms
• Machine Learning Techniques
• Next Generation Sequencing Analysis
• Programming Proficiency In R And Python

ATS Optimization Keywords

Hard Skills

• Multi-Omic Data Analysis
• Genomic Analysis
• Transcriptomic Analysis
• Proteomic Analysis
• Statistical Methods
• Computational Modeling
• Analytical Methodologies
• Data-Driven Research Initiatives
• Technical Documentation
• Program Management

Soft Skills

• Excellent Communication Skills
• Interpersonal Skills
• Presentation Skills
• Mentorship
• Team Leadership

Industry Keywords

• Cancer Research
• Bioinformatics
• Tumor Evolution
• Therapeutic Resistance
• Radiation-Related Phenotypes
• Clinico-Genomic Integration
• Spatial-Omics
• Biomarkers
• Translational Research
• Program Governance

Tools & Technologies

• Bioinformatics Software
• Statistical Software
• Computational Infrastructure
• Data Analysis Platforms
• Change-Management Tools