Website ConcertAI

Responsibilities

Work Experience

  • Work with internal teams to advance approaches that best utilize ConcertAI’s real world data (RWD) and technologies and provide solutions to ConcertAI’s clients.
  • Understand team goals and provide efficient analysis of clinical, SDOH, and NGS data for insights into practical genomic science solutions.
  • Conduct precision oncology services, i.e., patient stratification, phenotype discovery, molecular sub-typing, and biomarker discovery on data from clinical EMR, SDOH, and integrated NGS sources, using:
    • Basic statistics, e.g. descriptive, inferential, correlation, regression, and probability methods.
    • Convergence analyses.
    • Latent variable learning, e.g. EM, ICA, PCA, SVD, UMAP.
    • Spatial transcriptomics.
    • Supervised learning methods, e.g., CART, CNN, Cox regression models, GSEA.
    • Unsupervised learning methods, i.e. anomaly detection, cluster analysis, e.g. hierarchical, k-means, factor analysis, NMF, and/or SNF.
  • Contribute to our technology platform in collaboration with engineers.
  • Proactively communicate with internal experts from data curation, data products team and clinical experts to answer questions about our data.

Requirements

  • Good understanding of biological concepts
  • MS/PhD in a STEM field or equivalent experience, with training in biomedicine, biostatistics, machine learning, bioinformatics, and/or computational biology
  • Comfortable working in a fast-paced, changing, high-growth environment
  • Strong communication skills to present complex insights to teammates and/or clients
  • Working knowledge of programming languages Python and R
  • Experience with SQL
  • Enthusiasm for working with complex datasets in an interdisciplinary, team-playing role
  • 1+ years hands-on experience in analyzing messy real world data including genomics data
  • Subject matter expertise (oncology or RWD) or the drive to quickly learn these areas and the passion to deeply understand the data
  • Experience with using supervised and unsupervised learning methods

Preferred Qualifications

  • Experience with analyzing and deriving insights with whole slide imaging (WSI) data
  • 2+ years experience with building, or at least using, generative AI for work

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