Valo Health

Data Scientist II, Tissue Engineering

Remote

Not SpecifiedCompensation
Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Biotechnology, Pharmaceuticals, Health TechnologyIndustries

Requirements

A Ph.D. with 1-2 years of experience or a Master's degree with 3-4 years of experience, or comparable experience in a relevant computational science field like computational biology, bioengineering, or biostatistics is required. Candidates must possess a strong background in data processing and analysis, familiarity with statistics and machine learning techniques (including neural networks, generative models, ensemble learning, regression, classification, and regularization), proficiency in Python with data analysis libraries (Pandas, NumPy, SciPy, Scikit-learn, TensorFlow/PyTorch), and familiarity with version control systems like Gitlab or Github.

Responsibilities

Collaborate with biologists and computational scientists to visualize, preprocess, and analyze datasets from human tissue models and bioengineering experiments. Create clear data visualizations and statistical summaries to communicate findings to diverse audiences, including designing and building user interfaces. Develop predictive models and algorithms to identify factors affecting tissue model development, manufacturing, and use. Work with scientists and engineers to optimize experimental conditions and model in-vitro phenotypic responses to perturbations. Build models using large datasets to explain experimental variability and inform scientists on optimizing experiments and engineered tissue production through multivariate analyses, time series data processing, and other statistical and machine learning modeling techniques.

Skills

Data Science
Tissue Engineering
Drug Discovery
Computational Models
Engineered Tissue Assays
Statistical Models
Machine Learning
In Vitro Analysis

Valo Health

Drug discovery using machine learning technology

About Valo Health

Valo Health focuses on drug discovery and development in the biopharmaceutical sector, utilizing advanced technology to create new drugs and therapies. The company employs its proprietary Opal Computational platform, which integrates machine learning, tissue biology, and patient data to streamline the drug discovery process. This platform allows Valo Health to identify potential drug candidates more quickly and accurately than traditional methods. Valo Health differentiates itself from competitors by combining technology with life sciences, fostering a collaborative culture that addresses significant challenges in drug development. The company's goal is to improve health outcomes for patients worldwide by delivering effective solutions through partnerships with pharmaceutical companies and research institutions.

Boston, MassachusettsHeadquarters
2019Year Founded
$474.2MTotal Funding
LATE_VCCompany Stage
AI & Machine Learning, BiotechnologyIndustries
51-200Employees

Risks

Leadership changes may impact Valo's strategic direction and decision-making.
Heavy reliance on Novo Nordisk partnership poses financial risks if expectations aren't met.
Intensifying competition in AI-driven drug discovery could challenge Valo's market position.

Differentiation

Valo Health integrates AI and human-centric data for drug discovery and development.
The Opal Computational Platform offers an end-to-end solution for drug discovery.
Valo's approach combines machine learning, tissue biology, and patient data for precision therapeutics.

Upsides

Valo's partnership with Novo Nordisk could yield up to $4.6 billion in milestone payments.
The growing market for AI-driven drug discovery platforms supports Valo's business model.
Strategic partnerships with pharmaceutical companies enhance Valo's revenue and market reach.

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