Staff Data Scientist

Company: Series B Clinical Stage Biotech

Location: Boston MA

Role Overview: Staff Data Scientist

My client is seeking a Staff Data Scientist to analyze large datasets and developing methods to identify meaningful patterns from their proprietary database. This role will have a significant impact on early discovery, candidate development, and biomarker identification. The ideal candidate will thrive in a fast-paced, collaborative environment, working across multiple teams to build and implement computational solutions.

Key Responsibilities :

• Apply statistical techniques to explore complex biological data and identify meaningful relationships.
• Develop and implement analytical methods, models, workflows, and applications to support in-house research and development efforts.
• Analyze data from highly multiplexed experimental assays to find patterns and features.
• Contribute to the design, development, and optimization of machine learning models.
• Stay updated with scientific literature and apply knowledge to refine and benchmark new methods.
• Build data visualizations and user interfaces for experimental scientists.
• Support the processing and interpretation of next-generation sequencing (NGS) data, ensuring timely and accurate results.
• Communicate data insights effectively to various teams and provide continuous project updates.

Required Qualifications :

• Master’s degree in Data Science, Bioinformatics, Computational Biology, Machine Learning, Statistics, or a related field with 5+ years of experience (PhD preferred).
• Proficiency in handling and analyzing multi-dimensional datasets.
• Strong experience with Python and related analysis libraries (pandas, numpy, scipy).

Preferred Qualifications :

• Experience with next-generation sequencing data pipelines, including gene expression and single-cell data.
• Familiarity with machine learning model development and optimization.
• Expertise in deep generative models (e.g., VAEs, CNNs, GANs).
• Strong coding skills in Python, R, SQL, and bash scripting.
• Experience in cloud computing and AI frameworks like TensorFlow, Keras, or PyTorch.
• Experience with data visualization tools (e.g., matplotlib, seaborn, plotly, ggplot2) and app development using Python Streamlit or R Shiny.