Job Description:
Harbinger Health, a Flagship-founded company, is pioneering early cancer detection. Harbinger aims to detect cancer, at the earliest stages, to save lives. Our platform leverages proprietary biological insights and artificial intelligence to enable high-resolution, molecular views on cancer from blood. We are a highly dynamic, entrepreneurial, and innovation-driven organization seeking collaborative, passionate, and dedicated people to join our team.
Flagship Pioneering conceives, creates, resources, and develops first-in-category bioplatform companies to transform human health and sustainability. Since its launch in 2000, the firm has, through its Flagship Labs unit, applied its unique hypothesis-driven innovation process to originate and foster more than 100 scientific ventures, resulting in more than $200 billion in aggregate value. To date, Flagship has deployed over $2.5 billion in capital toward the founding and growth of its pioneering companies alongside more than $19 billion of follow-on investments from other institutions. The current Flagship ecosystem comprises 42 transformative companies, including Axcella Health (Nasdaq: AXLA), Codiak BioSciences (Nasdaq: CDAK) Denali Therapeutics (Nasdaq: DNLI), Evelo Biosciences (Nasdaq: EVLO), Foghorn Therapeutics (Nasdaq: FHTX), Indigo Ag, Kaleido Biosciences (Nasdaq: KLDO), Moderna (Nasdaq: MRNA), Omega Therapeutics (Nasdaq: OMGA), Rubius Therapeutics (Nasdaq: RUBY), Sana Biotechnology (Nasdaq: SANA), Seres Therapeutics (Nasdaq: MCRB), and Sigilon Therapeutics (Nasdaq: SGTX).
Position Summary
Harbinger Health is seeking a highly motivated and innovative Data Scientist to join our AI and Computational Biology group. The candidate will be responsible to create statistical models and machine learning models. In addition, the candidate will be responsible for analysis of raw data and model results. The candidate will also work on tools to help interpret and visualize raw data and model outputs. No prior knowledge of computational biology or experience in biotech industry is required. The candidate will be working closely with data scientists, machine learning engineers, bioinformatics group, and assay group. the candidate should have strong communication skills, attention to details and ability to work both independently and in a strong team environment.
Key responsibilities
- Mine and analyze large data sets
- Preprocessing of data sets and data clean up
- Develop statistical and predictive models on genomic and health related data sets
- Analyze genomic data for feature selection
- Investigate data sets and machine learning models for potential biases and covariates
- Coordinate with different functional teams to implement models and monitor outcomes
- Develop processes and tools to assess model performance and accuracy
- Work with stakeholders throughout the organization
Qualifications
- PhD or MSc + 5 years of experience in Computer Science, Statistics, Computational Biology, Scientific Computing or other relevant areas
- Proficient in Python language
- Working experience with Python modules for data science: Pandas, Scikit-Learn, Scipy, Numpy
- Familiar with machine learning modules in python such as PyTorch or Keras
- Knowledge of advanced statistical techniques and concepts (properties of distributions, statistical tests, regression, etc.), and experience with applications
- Knowledge of variety of machine learning techniques (clustering, decision trees, artificial neural networks, etc.)
- Familiarity with genomic data types is a plus
- Strong problem solving skills
- Strong communication and collaboration skills
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