Resume

SUMMARY

Data scientist experienced in developing analytical tools and workflows for drug discovery. Collaborates across scientific and engineering teams to translate complex questions into AI-enabled solutions. Expertise in LLM-based knowledge applications, large-scale biomedical data, and communicating with both technical and non-technical stakeholders to guide decisions.

EDUCATION

  • Ph.D., Integrative Biology: University of Wisconsin-Madison (2018)
  • B.S., Biopsychology (cum laude): Tufts University (2013)

TECHNICAL SKILLS

  • AI & ML: LLMs; tool-calling agentic workflows; LLM-based data extraction, interpretation, and prioritization; unsupervised clustering; dimensionality reduction (PCA, UMAP, t-SNE)
  • Software & Data Science: Python; R; Bash; SQL; Git; Markdown; Dash, Shiny; Quarto
  • HPC & Cloud: Linux; GCP; AWS
  • Scientific Domain Expertise: drug discovery; biomarker research workflows; single-cell transcriptomics; spatial transcriptomics; molecular biology; neuroscience

EXPERIENCE

Associate Consultant, Decision Analytics (Jul. 2025 – Present)
ZS Associates (Boston, MA)

Senior Scientist, Bioinformatics (Jan. 2022 – Oct. 2024)
Parexel International (Remote)

  • Improved latency of data delivery by 10x for a major pharmaceutical client by developing novel data ingestion pipelines in R, Python, and Bash to drive biomarker discovery
  • Collaborated across bioinformatics and data engineering teams to deliver 1000s of genomic datasets (GWAS & eQTL) scaling to terabytes in size, integrating data and metadata from UK Biobank, 1000 Genomes Project, FinnGen, Open Targets, GWAS Catalog, and more
  • Automated high-throughput quality control workflows to enable 24-hour client turnaround

Postdoctoral Researcher, Neuroscience (Jun. 2018 – Jan. 2022)
University of Texas Southwestern Medical Center (Dallas, TX)

  • Led a multi-group collaboration to publish novel single-cell RNA sequencing datasets in neuroscience, producing a co-first-author paper in Science (180+ citations), a second-author paper in Nature Communications (45+ citations), and a nationally-competitive NIH Postdoctoral Fellowship (F32)
  • Delivered spatial transcriptomics capabilities to research group, encompassing molecular library preparation, data and analytics pipelines, documentation, and training for new users

Graduate Researcher, Integrative Biology (Sep. 2013 – May 2018)
University of Wisconsin-Madison (Madison, WI)

  • Produced 5 first-author publications, 5 conference poster presentations, and a nationally-competitive NSF Graduate Research Fellowship
  • Applied multiple linear regression techniques to analyze gene expression, protein labeling, and behavioral data from molecular biology experiments in neuroscience (quantitative PCR, in situ hybridization, immunohistochemistry, and confocal microscopy)

INDEPENDENT PROJECTS

Crystal: A structured knowledge pipeline for scientific discovery
2026 — https://dmerullo.github.io/crystal-pipeline

  • Applied LLMs to transform unstructured text from scientific publications into a graph representation of concepts and relationships, surfacing structural connections and knowledge gaps not seen in keyword search and citation networks
  • Validated the approach against neuroscience literature, using domain expertise to confirm results (e.g., SRPX2 & SLIT1 in sensorimotor learning) as genuine knowledge gaps
  • Generalized the architecture into a domain-agnostic system, demonstrating applicability to recommendation and discovery problems more broadly

Project ESPAÑOL: Exploring Spanish-language Poetry And Nuances Of Language
2024 — https://dmerullo.github.io/project-espanol

  • Generated a dataset of 10,000+ Spanish-language poems (>2.5 million words) using high-throughput web scraping (rvest)
  • Developed an unsupervised clustering pipeline in Python to classify poems into 4 difficultly levels based on verb usage
  • Built an interactive web application enabling language learners to explore and identify level-appropriate Spanish texts

SELECTED PUBLICATIONS (2 of 12; 800+ citations total)

  • Colquitt, B. M.*, Merullo, D. P.*, Konopka, G., Roberts, T. F., & Brainard, M. S. (2021). Cellular transcriptomics reveals evolutionary identities of songbird vocal circuits. Science, 371(6530), eabd9704. *co-first author

  • Xiao, L., Merullo, D. P., Koch, T. M. I., Cao, M., Co, M., Kulkarni, A., Konopka, G., & Roberts, T. F. (2021). Expression of FoxP2 in the basal ganglia regulates vocal motor sequences in the adult songbird. Nature Communications, 12(1), 2617.