Biological Dynamics, Inc. is a healthcare company committed to improving global health outcomes by detecting diseases in their earliest stages. Founded in 2010, based on a discovery developed at UC San Diego’s Jacobs School of Engineering, the company is in the process of developing diagnostic solutions that will lead to better ways to screen, diagnose, and manage high burden conditions. Our proprietary isolation platform simplifies access to native-state biomarkers and nanoparticles, enabling multiomics applications.
We are building a portfolio of novel oncology products designed to enable early detection and individualized treatment response monitoring. In addition to lab-focused products, our affordable smartphone-enabled point-of-care diagnostic solutions bring blood-based DNA testing into the home to improve human health.
In your position as Lead Data Scientist you will be leading a newly-formed interdisciplinary Data Science team. Your team will be tasked with developing deep machine learning models and corresponding data infrastructure to analyze large multi-dimensional datasets. Your analysis of complex genomic, multi-omic, clinical, and phenotypical datasets will advance discoveries in early cancer detection, neuroscience, and infectious disease; it will also inform our manufacturing, product and commercial strategy.
Essential Job Duties
- Lead, develop, and manage a Data Science team.
- In close collaboration with scientific teams, develop machine learning and statistical methods to analyze multi-omic data to advance Early Cancer Detection program and biomarker discovery for oncology and neuroscience.
- Develop and oversee the implementation of a formal objective process for selecting and qualifying ML frameworks for each of the applications.
- Oversee the all phases of development for data science-based projects from exploration and conceptualization to developing and testing of the models.
- Oversee the technical team that will be developing the data infrastructure to support machine-learning initiatives. Oversee the implementation of the formal process pipeline. Develop ML-based solutions for as well as monitoring, debugging, and continuous improvement of the implemented solutions.
- Play a leadership role in development of research protocols, statistical analysis plans, and other relevant documentation packages. Ensure accuracy and statistical validity of assigned deliverables.
- Develop deep understanding how data science projects fit within Biological Dynamics overall strategy. Provide technical leadership across organization, contribute to cross functional projects.
- Communicate of key findings at internal and external meetings, as well as contribute to publications.
- Ph.D. in Bioinformatics, Computational Biology, Statistics, Biological Sciences, Cancer Biology, Genetics, Genomics, Computer Science, Physics, or equivalent experience.
- 10 year(s)+ industry experience, ideally with 5 years of experience in biological applications of AI/ML
- Min 3 years of experience managing data science team, or equivalent experience.
- Deep understanding of modern statistical and machine learning tools used for analysis of genomics and multi-omic datasets.
- Familiarity with Deep Learning, Neural Networks, Embeddings, Transfer Learning, Data Visualization tools and dimensionality reduction
- Familiarity with some of deep learning libraries such as Keras, TensorFlow, and PyTorch
- Demonstrated expertise in at least one programming language (R, Python, Go, C++).
- Proficient in databases (SQL, Postgres preferred)
- Proficiency in experiments design, reproducible research practices, version control tools.
- Technical leadership and self-direction, willingness to both teach others and learn new techniques.
- Effective written and verbal communication skills
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