Associate Director, Data Science

Scorpion Therapeutics; Boston (MA); On-site; USD 180,000 - 230,000; Full time

Job summary

Scorpion Therapeutics is seeking an Associate Director to advance translational genome analytics within its data science team. You will work on reverse translation from clinical data to discover biomarkers and inform combination strategies in molecularly defined populations.

You will analyze large multimodal datasets (bulk RNA-seq, WES/WGS, imaging, proteomics) and apply deep learning/AI to identify predictive biomarkers for clinical outcomes, collaborating with AIML teams building foundation

Qualifications

• Statistical learning and data mining expertise for integrative analysis of multimodal, high-dimensional molecular profiling datasets.
• Hands-on experience with large genetic/genomic/immunogenomic/clinical datasets (e.g., TCGA, GTEx, DepMap).
• Proficiency coding in R/Python and/or MATLAB with reproducible-analysis best practices.
• Strong communication/presentation skills; ability to guide decisions with data-driven hypotheses.
• Independent, flexible, collaborative mindset.

Responsibilities

• Perform reverse translation from clinical datasets to enable biomarker discovery and target identification.
• Analyze, summarize, and visualize findings from multi-modal clinico-genomic datasets.
• Use deep learning/AI and multivariate predictive modeling to identify biomarkers for outcomes.
• Collaborate with AIML teams developing foundation models trained on large cohorts.

Skills

Statistical Learning

Data Mining

Genomic Data

R

Python

MATLAB

Communication

Collaboration

Education

Master's degree in quantitative field

PhD in quantitative field

Tools

MATLAB

Python

R

Job description

The Translational Genome Analytics group is recruiting an Associate Director (Associate Principal Scientist) to join its data science team.

Responsibilities

• Perform reverse translation from clinical datasets to enable biomarker discovery, combination strategies, and novel target identification for molecularly defined patient populations.
• Analyze, summarize, and visualize findings from large multi-modal clinico-genomic datasets (bulk RNA-seq, WES/WGS, imaging, epigenetic profiling, single-cell RNA-seq, proteomics).
• Use deep learning/AI and multivariate predictive modeling to discover novel biomarkers predictive of clinical outcomes; apply statistical inference and/or deep learning to integrative analysis of multimodal, high-dimensional tumor profiling data.
• Collaborate with AIML teams developing foundation models trained on large cohorts of human data.

Qualifications

• Master’s (8+ years) or Ph.D. (4+ years) in a quantitative field (e.g., Engineering, Applied Physics/Mathematics, Bioinformatics, Computational Biology) with substantial computational/statistical experience.

Required Experience/Skills

• Statistical learning and data mining expertise for integrative analysis of multimodal, high-dimensional molecular profiling datasets in oncology/immuno-oncology.
• Hands-on experience with large genetic/genomic/immunogenomic/clinical datasets (e.g., IEDB, TCGA, GTEx, DepMap).
• Proficiency coding in R/Python and/or MATLAB with reproducible-analysis best practices.
• Strong communication/presentation skills; ability to guide decisions with data-driven hypotheses.
• Independent, flexible, collaborative mindset.

Preferred

• Clinical-trials genomic analysis; cancer biology knowledge; cross-disciplinary collaboration in matrix environments; high-profile publications.

Skills

• Cancer Biology
• Computational Biology
• Data Analysis
• Data Mining
• Data Science
• Genomic Data Analysis
• Immuno-Oncology
• MATLAB
• Multimodal Analysis
• Python
• R
• Statistical Analysis
• Statistical Learning