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# Salesforce Developer

- **Company:** CareerCircle
- **Location:** Cambridge, MA, United States
- **Salary:** $176,200.0 - $277,300.0
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Artificial Intelligence, Algorithm Design, Amazon Web Services, Business Analytics Applications, Data Analysis, Bioinformatics, Software as a Service, Cloud Computing, Profiling, Computational Biology, Computer Simulation, Image Analysis, Directed Acyclic Graph (Directed Graphs), Data Transmissions, Information Engineering, Data Infrastructure, Data Stores, Data Visualization, Linux, R (Programming Language), Statistical Hypothesis Testing, Infrastructure as a Service (IaaS), Python (Programming Language), Linux System Administration, Machine Learning, Natural Language Processing, Platform as a Service (PAAS), Scrum Methodology, Scala (Programming Language), Software Engineering, SQL Databases, Systems Integration, Visual Analytics, Enterprise Software Applications, Cloud Platform System, Transfer Learning, Large Language Models, Deep Learning, Generative AI, Git, Information Technology, Software Version Control, Programming Languages
- **Published:** September 3, 2026
- **Apply:** https://www.careercircle.com/jobs/all/all/usa/ca/south-san-francisco/53832f5b-9b0f-4136-8e07-35087ac85547

## About the Role

Triage
Writing
Biology
Research
Genetics
Genomics
Barcoding
Pipelines
Mentorship
Innovation
Immunology
Statistics
Compassion
Proteomics
Biophysics
Mathematics
Scalability
Phenotyping
Data Science
Data Analysis
Biostatistics
Data Modeling
Deep Learning
Cell Cultures
Prioritization
Bioinformatics
Image Analysis
Version Control
Cloud Computing
Small Molecules
Disease Biology
Gene Expression
Computer Science
Algorithm Design
Machine Learning
Telephone Skills
Data Engineering, * MS in computational biology, bioinformatics, biostatistics, biophysics, mathematics, statistics, genetics/genomics, computer science or a related STEM discipline and a minimum of 8 years of relevant professional experience, including hands on experience analyzing large scale NGS and functional genomics datasets.

 * A passion for solving biological problems through computational methods with a proactive focus on details and execution.
 * Experience with the computational analysis, algorithm development, and biological interpretation of large scale NGS and functional genomics datasets.
 * A proven track record of applying machine learning to analyze single cell RNA sequencing data to identify novel patterns and functional insights.
 * Previous experience with experimental design of biological assays, statistical hypothesis testing, and integrating results from multiple omics data sources.
 * Proficiency in at least one statistical programming language such as R or Python, along with experience using version control environments like Git.
 * Familiarity with public data repositories like The Cancer Genome Atlas, Dependency Map, Cancer Cell Line Encyclopedia, and Clinical Proteomic Tumor Analysis Consortium.
 * Experience with AWS cloud computing infrastructure and Linux environments.
 * Excellent oral and written communication skills., * A Ph.D. in Bioinformatics, Biostatistics, Computational Biology, Statistics, Computer Science, Mathematics, Biophysics, Genetics/Genomics, or a related STEM field with 4+ years of professional experience.
 * A strong background with post doctoral or relevant industry experience, including prior experience leading an analytics team and mentoring scientists.
 * Substantial computational experience specifically with functional genomics data, including CRISPR screen hit calling frameworks and library design interpretation.
 * Experience with optical pooled CRISPR screening image analysis pipelines and integrating morphological readouts with genomic datasets.
 * Expertise applying deep learning approaches to image based phenotypic profiling and cell classification for target identification.
 * Deep understanding of general disease biology and immunology, with knowledge of the latest functional genomics research.
 * Expertise in utilizing network-based analysis frameworks or transfer learning techniques to infer gene regulatory patterns from NGS datasets.
 * Hands on experience building or deploying LLM powered systems or AI tools for biological data interrogation.
 * Experience developing interactive data visualization tools, for example R Shiny, for multiomics readouts.
 * A track record of developing novel functional genomics methods, demonstrated through first author publications or released tools.

Travel

Up to 10% travel is required., Amazon Web Services (AWS), Bioinformatics, Biological Data Analysis, Computational Biology, Computational Genomics, CRISPR-Cas System, Data Engineering, Data Modeling, Data Science, Data Visualization, Gene Expression Profiling, Genome, Genome Sequencing, Genomic Analysis, Genomics, Machine Learning (ML), Omics, RNA-Seq, Single-Cell Genomics, Software Development, Writing
Biology
Research
Genetics
Genomics
Barcoding
Pipelines
Mentorship
Innovation
Immunology
Statistics
Compassion
Proteomics
Biophysics
Mathematics
Scalability
Phenotyping
Data Science
Data Analysis
Biostatistics
Data Modeling
Deep Learning
Cell Cultures
Prioritization
Bioinformatics
Image Analysis
Version Control
Cloud Computing
Small Molecules
Disease Biology
Gene Expression
Computer Science
Algorithm Design
Machine Learning
Telephone Skills
Data Engineering, Linux
Triage
Writing
Biology
Research
Genetics
Genomics
Barcoding
Pipelines
Mentorship
Innovation
Immunology
Statistics
Compassion
Proteomics
Biophysics
Mathematics
Scalability
Phenotyping
Data Science
Data Analysis
Biostatistics
Data Modeling
Deep Learning
Cell Cultures
Prioritization
Bioinformatics
Image Analysis
Version Control
Cloud Computing
Small Molecules
Disease Biology
Gene Expression
Computer Science
Algorithm Design
Machine Learning
Telephone Skills
Data Engineering, Ideation
Backlogs
Usability
Visionary
Automation
Governance
Innovation
Creativity
Ethical AI
Scalability
Informatics
Market Trend
Data Science
Digital Data
Communication
Data Analysis
Deep Learning
User Research
User Feedback
Responsible AI
Pharmaceuticals
Decision Making
Design Thinking
Open Innovation
Customer Service
Product Strategy
Product Roadmaps
Machine Learning
Business Metrics
Agile Methodology
Influencing Skills
Value Propositions
Advanced Analytics
Product Management
Performance Metric

## Description

Transfer Learning
Edge Intelligence
Biopharmaceuticals
Data Visualization
Workflow Management
Amazon Web Services
Predictive Modeling
Experimental Design
Functional Genomics
Software Engineering
Contingent Workforce
Computational Biology
Computational Genomics
Artificial Intelligence
Statistical Programming
Whole Genome Sequencing
R (Programming Language)
Applied Machine Learning
Ribonucleic Acid Sequencing
Python (Programming Language)
Statistical Hypothesis Testing
Directed Acyclic Graph (Directed Graphs), Our company is a global health care leader committed to being the world's premier research intensive biopharmaceutical company. Our Research Laboratories will take our leading discovery capabilities and world class small molecule and biologics research and development expertise to create breakthrough science that radically changes how we approach serious diseases.

The Data, AI and Genome Sciences (DAGS) department seeks a talented computational biologist for our Translational Genome Analytics (TGA) team. In this role, you will lead our Functional Genomics & Predictive Modeling function, shaping how its evidence is generated, interpreted, and integrated across the discovery portfolio. You will own the computational and modeling frameworks that range from hit calling for our perturbational screens to multi-evidence integration to prioritize targets and/or drug combinations. You will serve as a technical and scientific leader who shapes early discovery direction, mentors a team of scientists, and applies cutting edge AI and ML to accelerate how we turn data into decisions.

This is a rare opportunity to build and lead a functional genomics analytics capability from the ground up, where your team's calls directly shape which targets advance in our discovery portfolio, one of the most exciting frontiers in computational biology today.

In This Exciting Role You Will

 * Lead the design and build of scalable computational analytics frameworks for pooled, arrayed, single cell, and optical CRISPR screens, from QC pipelines and library design to longitudinal readout analysis.
 * Invent and scale computational methods for the next generation of functional genomics, spanning scalable single cell perturbation screening, cellular barcoding, and lineage tracing, to elucidate adaptive resistance mechanisms and drug combinations.
 * Build image analysis pipelines for high content and optical CRISPR screens, turning morphological phenotypes into biological insight that guides target prioritization.
 * Integrate functional genomics and imaging derived results with high throughput transcriptomics and proteomics datasets to build multi evidence target prioritization packages for multiple stages of drug discovery.
 * Bring modern AI and ML, including LLM powered agentic workflows and network based methods, to how we triage targets and synthesize biological evidence.
 * Lead and mentor a team of scientists, set the technical direction for functional genomics analytics, and drive standards for reproducible research and FAIR data infrastructure.
 * Collaborate across disciplines with experimental scientists, software engineers, and external partners to advance shared analytical platforms and support Therapeutic Area target identification., Transfer Learning
Edge Intelligence
Biopharmaceuticals
Data Visualization
Workflow Management
Amazon Web Services
Predictive Modeling
Experimental Design
Functional Genomics
Software Engineering
Contingent Workforce
Computational Biology
Computational Genomics
Artificial Intelligence
Statistical Programming
Whole Genome Sequencing
R (Programming Language)
Applied Machine Learning
Ribonucleic Acid Sequencing
Python (Programming Language)
Statistical Hypothesis Testing
Directed Acyclic Graph (Directed Graphs)
+0

Google IT Automation with Python, Government Affairs
Customer Engagement
Software Development
Product Requirements
Programming Languages
Digital Transformation
Intelligent Automation
Continuous Development
Artificial Intelligence
R (Programming Language)
SQL (Programming Language)
Engineering Design Process
Software As A Service (SaaS)
Platform As A Service (PaaS)
Product Lifecycle Management
Scrum (Software Development)
Scala (Programming Language)
Python (Programming Language)
Ethical Standards And Conduct
User Acceptance Testing (UAT)
Influencing Without Authority
Product Requirements Documents
Enterprise Application Software
Natural Language Processing (NLP)
Collaborative Innovation Networks
Generative Artificial Intelligence
Infrastructure As A Service (IaaS)
Master Of Business Administration (MBA)
Artificial Intelligence Product Management
+0


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