Role overview

We are hiring a Data Scientist who is excited to derive deep insights from novel types of spatial biology datasets, and directly impact development of our integrated measurements platform, ensuring we generate the highest value data. Our core technology captures unique pairings of high-resolution image data, protein measurements, RNA-FISH, and spatial NGS data from intact biological tissues. You will have the opportunity to work with these datasets to select, pilot, and optimize core bioinformatic and advanced spatial-omic analysis methods. You will also work to build models for efficient spatial inference for development of our next-gen technology. Through a deep understanding of our data types, volume, and quality, you will help to refine our overall data model to support platform standardization and our data collection strategy. 

We are a very integrated team and platform, and a propensity to work collaboratively and openly share plans, progress, and insights is key. You will work closely with scientists to provide input on experimental protocol design and to support scientist-driven data analyses, partner reports, and shareable data packages. You will also work closely with software and data engineers to access and contribute analytical tools and data pipelines into our shared code base. 

Core Responsibilities

• Independently develop and apply computational techniques to derive insights from large multimodal datasets, for identification of biomarkers and characterization of cell-cell interactions
• Develop and apply NGS analysis modules to characterize reads from various sequencing platforms, quantify statistical events (e.g. read structures, gene expression, isoforms, SNPs) and perform core bioinformatic and QC analyses
• Help lead data governance efforts, maintaining accurate data models to ensure organization-wide understanding of analyses
• Develop image analysis methods to quantify IHC and RNA-FISH data, and characterize morphological features
• Develop methods for efficient spatial inference as part of DB’s spatialomics technology development
• Provide guidance on experimental protocol design geared toward powering data insights, including scale and quality thresholds
• Support scientists in generating insights reports for pharma partners
• Identify external datasets of value, and work with engineers to define strategies for ingestion, processing, and quality control of external data sets

Additional Responsibilities

• Work closely with lab and software teams in development and deployment of analyses
• Prepare reports for internal and external communication of results
• Inform best practices and tutorials for Scientist-driven data analyses

Required Qualifications

• PhD in Data Science, Computational Biology, Statistics, Bioinformatics, or a related field
• Proven experience in developing and applying statistical methods to NGS data, spatial transcriptomics and/or spatial high content imaging data
• Experience in building analysis workflows
• Fluency in Python

Preferred Qualifications

• Fluency with Git and DevOps best-practices
• Experience with both AI-based and “traditional” image analysis techniques
• Molecular biology research experience is highly desirable