Our well funded biotech partner is seeking a Computational Data Scientist to join their team to help to enable new insights into drug discovery and development. The ideal candidate will have a quantitative background with strong problem solving skills who is excited to analyze large multi-dimensional datasets to drive solutions within drug development.
Responsibilities:
- Use statistical techniques to uncover relationships in complex biological data and identify patterns in multiplexed assay results.
- Build, evaluate, and implement analytical methods, workflows, and machine-learning models for discovery and development.
- Assist wet lab scientists with visualizations, user interfaces, and NGS data interpretation, ensuring timely results.
Qualifications:
- Masters or PhD in Math, Data Science, Bioinformatics, or related fields with 3+ years of experience.
- Skilled in analyzing multi-dimensional datasets (NGS), proficient in Python analyses (pandas, numpy, scipy).
- Experienced in principal component analysis, multivariate regressions, ANOVA, Bayesian statistics, and biological applications.
- Familiar with ML and deep generative models (e.g., VAEs, GANs, CNNs)
- Proficient in Python, R, SQL, bash, and AI frameworks (TensorFlow, PyTorch, sklearn).
