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A Field Bioinformatics Scientist (FBS) is a bioinformatics expert who provides data analysis and technical support to customers and internal stakeholders. The FBS is responsible for educating customers on the data processing and analysis tools provided by Pixelgen as well as troubleshooting any technical issues that may arise. A lot of the time the FBS plays a crucial role in advising customers on design of experiment and how to get the best value from their Pixelgen data.
Job Responsibility:
Support customers in their journey from experimental design to analyzed data with a focus on data processing and analysis
At times, analyze single-cell Proximity Network data as part of service offering for customers
Train new customers on the Pixelgen data processing and analysis tools
Troubleshooting technical issues by interacting with customers, looking at customer data and identifying and resolving technical issues that customers may encounter
Providing product performance, customer needs and market trends feedback to the company
Managing customer relationships through building and managing strong relationships with our customers to ensure their needs are met and to identify opportunities for new business.
Support other company functions with data analysis and bioinformatics expertise
Present scientific results from analysis to internal and external stakeholders through written reports, visualizations, and oral presentations.
Managing customer issue ticketing systems and helping to develop a system that works well and scales for Pixelgen.
Support pre-sales activities
Prepare and present technical seminars to existing and prospective customers
Travel up to 20% of the time.
Stay current with developments in single-cell data analysis, sequencing technology, proteomics methods, and multi-omics integration
Requirements:
MSc or PhD in bioinformatics, computational biology, systems biology, immunology, biotechnology, or a related field
Demonstrated experience with single-cell omics data analysis
Strong programming skills in R and/or Python, and experience with Linux-based environments
Solid understanding and hands-on experience with data analysis methods, including dimensionality reduction, clustering, and batch correction
Applies appropriate statistical methods to draw conclusions from data
Proficiency in data visualization tools, using best practices to communicate complex findings effectively
Excellent communication skills and ability to collaborate across disciplines.
Nice to have:
Experience in direct support of customers in academia or industry
Experience in research (e.g. PhD degree or similar). In particular from immunology, hematology, proteomics, systems biology, or spatial omics fields
Experience with next-generation sequencing data
Experience with training others on bioinformatics tools
In-depth knowledge of bioinformatics analysis workflows, especially in the fields of single-cell, proteomics, spatial omics, and multi-omics integration
Experience with creating and maintaining packages in R and/or Python
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