Data Scientist I

Evozyne is an AI-driven protein engineering company developing novel protein therapeutics across a wide range of diseases.

In this contract role, you will support experimental programs by delivering clean, reproducible analyses of biological data. You will partner closely with experimental scientists to understand assay design, wrangle multi-assay datasets, build decision-grade plots and summaries, and translate results for audiences from bench scientists to leadership. Your work will directly support experimental decision-making and generate high-quality datasets for model training (GenAI) for the design of novel synthetic biomolecules.

Location : This is a hybrid role, working 3 days per week onsite at our Chicago office.

What You'll Do

• Ingest, clean, and join large multi-plate experimental datasets (e.g., biochemical assays, plate maps, metadata) using Python (pandas, numpy).
• Implement repeatable analyses via notebooks and scripts.
• Select the right summary / metric for the biology and assay geometry and documents the rationale.
• Implement QA / QC checks (sanity checks, outlier flags).
• Produce decision-grade visualizations and concise exploratory data analysis (EDA) summaries.
• Package and share results with clear documentation.
• Collaborate extensively with experimental scientists - asking questions, reflecting on objectives, and agreeing on success criteria before executing.
• Translate technical results to the right abstraction level.
• Deliver analyses that directly inform next-step experiments, assay optimization, or go / no-go decisions.

Who You Are

You thrive in an early-stage start-up environment, leveraging your agility and expertise to deliver high-quality results. You are naturally curious and excel when working collaboratively to solve tough problems. You enjoy turning noisy experimental readouts into clean, decision-ready analyses for scientists and leadership.

Required Skills + Experience

• Master's degree in relevant technical discipline with limited prior industry experience or bachelor's degree in relevant technical discipline with 2+ years of industry experience.
• 1-3 years' experience analyzing experimental, biological, chemistry, or physics datasets (industry, startup, or academic lab).
• Ability to understand experimental context (read protocols, interpret assay outputs) and partner effectively with experimentalists.
• Advanced skills in Python data stack : pandas, numpy, data visualization, Jupyter workflows.
• Solid grasp of EDA and basic statistics (distributions, confidence intervals, hypothesis testing).