1

Executive Computer Science Bioinformatics Jobs in New York

Sc. plus a minimum of 3 years' experience in Bioinformatics, Computer Science, Programming, Software Development, or related field Previous experience with NGS data and associated bioinformatics ...

next page

Showing results 1-20

Executive Computer Science Bioinformatics information

What is the difference between Executive Computer Science Bioinformatics vs Data Scientist?

AspectExecutive Computer Science BioinformaticsData Scientist
Required CredentialsAdvanced degrees in bioinformatics, computer science, or related fields; often with leadership experienceDegree in computer science, statistics, or related fields; certifications like Certified Analytics Professional (CAP) are common
Work EnvironmentResearch labs, biotech firms, healthcare organizations, often in leadership rolesTech companies, finance, healthcare, with focus on data analysis and modeling
Employer & Industry UsageBiotech, pharmaceuticals, healthcare industry, often in executive or strategic rolesVarious industries including tech, finance, healthcare, focusing on data insights

Executive Computer Science Bioinformatics professionals typically hold leadership roles in biotech and healthcare, focusing on strategic decision-making, while Data Scientists analyze data across multiple industries to generate insights. Both roles require strong technical skills, but their focus and work environment differ significantly.

What is the highest paying job in bioinformatics?

In bioinformatics, senior roles such as Bioinformatics Directors or Principal Scientists typically have the highest salaries, often exceeding $150,000 annually. These positions require advanced skills in data analysis, programming, and leadership, and often involve managing large datasets and interdisciplinary teams.

Is computer science dead due to AI?

Computer science remains a vital field for roles like executive bioinformatics, as AI tools enhance data analysis and algorithm development. While AI automates certain tasks, expertise in programming, data management, and algorithm design continues to be essential for innovation and problem-solving in the industry.

Is AI going to replace bioinformatics?

AI is a tool that enhances bioinformatics by automating data analysis and pattern recognition, but it is unlikely to fully replace bioinformatics professionals. Bioinformatics roles require domain expertise, interpretation of complex biological data, and integration of AI tools with biological knowledge. Professionals in this field should develop skills in programming, machine learning, and biological sciences to stay relevant as AI advances.
What are the most commonly searched types of Computer Science Bioinformatics jobs in New York? The most popular types of Computer Science Bioinformatics jobs in New York are:
Software Engineer II - Bioinformatics R&D - Remote

Software Engineer II - Bioinformatics R&D - Remote

SEMA4

Stamford, CT โ€ข On-site, Remote

Full-time

Posted 7 days ago


Job description

Sema4 is a patient-centered health intelligence company dedicated to advancing healthcare through data-driven insights. Sema4 is transforming healthcare by applying AI and machine learning to multidimensional, longitudinal clinical and genomic data to build dynamic models of human health and defining optimal, individualized health trajectories. Centrellisยฎ, our innovative health intelligence platform, is enabling us to generate a more complete understanding of disease and wellness and to provide science-driven solutions to the most pressing medical needs. Sema4 believes that patients should be treated as partners, and that data should be shared for the benefit of all.
Sema4 is seeking a talented, self-motivated Software Engineer II - Bioinformatics R&D to contribute to cutting-edge translational bioinformatics and clinical product development. As a member of the R&D Bioinformatics department, you will act as a critical member of the Sema4 clinical and research ecosystem focused on innovation, reliability, and quality analysis of high-throughput data at an unprecedented scale. You will use advanced cloud computing technologies to do big data analytics. You will be part of an interdisciplinary team that develops computational methods and pipelines to interpret large-scale human genome and transcriptome sequencing data to understand mutations and mutation processes in cancer and reproductive health and to translate that understanding to clinical utility. You will develop systems for integrating novel informatics and genomics tools and methodologies into clinical products and practices.
RESPONSIBILITIES
  • Carry out software design, coding, testing, debugging, and documentation
  • Automate existing analysis workflows, migrate existing workflows to cloud platforms, and develop new workflows and pipelines for clinical and research projects
  • Develop, implement, and follow best practices in software development, code versioning, software testing, and deployment
  • Collaborate closely with scientists, clinicians, and product managers to design, engineer, and implement analytics pipeline solutions in the Amazon AWS cloud environment
  • Deliver high-quality, well-tested software to the production bioinformatics team for use in clinical products
  • Contribute to bioinformatics research analysis
  • Communicate effectively with collaborators (computational and bioinformatics scientists on R&D and production teams, IT/HPC, clinical lab directors, knowledgebase and curation teams, wet lab staff) to understand and satisfy product and research analysis needs
  • Train and provide support for bioinformatics scientists and other team members in internally developed best practices for software development, testing, and software development lifecycle (SDLC) policies

QUALIFICATIONS
  • M.S. in Computer Science, Computer Engineering, Bioinformatics, Computational Biology, or related fields. B.S. plus equivalent experience will be considered
  • 2+ years of post-graduate software development experience
  • Working in a team, self-motivation, ability to manage multiple tasks simultaneously, ability to solve problems independently
  • Possess strong understanding of computer science fundamentals, algorithms, and software engineering best practices
  • Strong coding proficiency in Python and R programming languages or similar. Experience with multiple coding languages such as Java/Scala is preferred.
  • Programming experience in Unix/Linux environment
  • Experience with Docker or similar software container platform
  • Hands-on experience working with NGS and bioinformatics tools will be a plus, especially GATK and WDL and common NGS data formats (VCF, BAM)
  • Experience working with cloud computing infrastructures will be a plus, especially on Amazon AWS and DNAnexus
  • Developing codebases using distributed version control tools (especially Git) and software issue tracking systems (especially Jira)
  • Excellent communication and interpersonal skills needed for working in an interdisciplinary team of scientists, engineers, and clinicians
  • Well-versed in the art of effective technical communication, especially graphical communication, about systems design and high-complexity datasets