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.