ProFound Therapeutics: Bioinformatics Data Engineering Co-Op

Flagship Pioneering • Cambridge, MA

17h • Hybrid

About The Position

ProFound Therapeutics is seeking a Bioinformatics Data Engineering Co-Op for a full-time, 4–6 month term from January 2027 to June 2027. The position is open exclusively to current Northeastern University Co-Op students and is based in Watertown, Massachusetts, with a hybrid schedule. The Co-Op will work on production bioinformatics pipelines and datasets, receive code review and mentorship, own a scoped project from start to finish, and present the project to the team. The role includes direct collaboration with scientists and provides hands-on experience in production bioinformatics and data engineering in an industry drug discovery setting.

ProFound Therapeutics discovers novel proteins across the expanded human proteome to identify therapeutic targets and develop medicines. Its ProFoundry Platform combines protein detection, validation, and computational technologies. The company uses proteomics, high-throughput experimental biology, and causal agentic AI to characterize proteins and advance drug discovery programs.

The Co-Op may work on projects such as a QC dashboard, pipeline benchmark, annotation resource, or statistics module. Duties include running and monitoring sequencing and proteomics pipelines, developing and validating QC checks, analyzing proteomics evidence, writing reusable scripts, contributing to a data catalog, and building scientist-facing visualization tools. The Co-Op will document work and present results, including a final presentation.

The Flagship Pioneering Co-Op Program also offers enrichment sessions, a professional development track, and a mentor. Students gain exposure to how Flagship builds companies and may be considered for future opportunities across Flagship and its portfolio companies. The role pays $25–$35 per hour. It is a short-term engagement and is not eligible for health and welfare benefits; retirement benefits may be available after a specified number of hours.

Requirements

• Be currently pursuing a B.S. or M.S. in Bioinformatics, Computational Biology, Biology, Biochemistry, Computer Science, or a related field.
• Be available for a full-time, 4–6 month Co-Op term.
• Have Python experience, including pandas, and comfort with the Linux command line.
• Know Git and demonstrate a habit of writing clear, tested, reproducible code.
• Have coursework or project experience in genomics or molecular biology, such as RNA-seq, translation, protein or DNA sequence analysis, or proteomics basics.
• Have clear written communication skills and document work.

Nice To Haves

• Basic R skills.
• SQL skills.
• Experience with Nextflow, Snakemake, Airflow, or another workflow manager, and Docker.
• Exposure to AWS services such as S3, EC2, or Athena.
• Familiarity with Ribo-seq, long-read sequencing, or mass spectrometry data, including peptides, PSMs, and database search.
• Basic statistics knowledge, such as differential expression, false discovery rate, and multiple-testing correction.
• A dashboard or web app built with tools such as Dash, Streamlit, or Shiny, linked from GitHub or a portfolio.
• Experience using AI coding assistants such as Claude Code, Copilot, or Cursor on real projects, with an understanding of their strengths and limitations.
• Exposure to LLM APIs, agents, MCP, or classic machine learning such as scikit-learn or PyTorch applied to biological data.

Responsibilities

• Run and monitor Nextflow pipelines for ribosome profiling (Ribo-seq), long-read sequencing, and DIA proteomics on AWS Batch.
• Triage failed jobs and summarize quality control using MultiQC and alignment metrics.
• Build and validate QC processes, including flagging samples that fail thresholds, comparing results across GENCODE versions, and writing automated checks for suspicious or missing experiment data.
• Analyze proteomics evidence, including peptide-to-protein mapping, sequence coverage, FDR-filtered evidence, and comparisons across search engines and experiments.
• Write and test Python and R scripts to parse, filter, and summarize FASTA, GTF, BAM, peptide, and protein-table outputs into Parquet or TSV.
• Turn exploratory notebooks into reusable, version-controlled code.
• Ingest or update datasets in the data catalog, document schemas, and check data using Athena SQL queries.
• Prototype visualizations or dashboards for scientists to review targets and QC results.
• Write READMEs and runbooks, share results in team meetings, and deliver a final Co-Op presentation.
• Own a scoped project from start to finish and work directly with scientists who use the resulting tools or data.

Benefits

• Professional development track and enrichment sessions through the Flagship Pioneering Co-Op Program.
• Mentorship.
• Potential consideration for future opportunities across Flagship and its portfolio companies.
• Hourly compensation of $25–$35.
• Retirement benefits may be available after completing a set number of hours.

What This Job Offers

• Job Type: Full-time
• Career Level: Intern
• Education Level: No Education Listed