Data Scientist - In Vitro Modeling

Salary: Not Specified Location Type: Not Specified Employment Type: Not Specified

About Us

Valo Health is a technology company dedicated to accelerating the creation of life-changing drugs for more patients faster by integrating human-centric data and AI-powered technology. We believe the drug discovery and development process can be significantly improved in terms of speed, cost, and success probability. Valo utilizes early-stage models to reduce failures, executes clinical trials for company valuation, and generates fit-for-purpose data to feed back into its Opal Computational Platform™, fundamentally reinventing drug discovery and development.

Our multi-disciplinary team comprises experts in science, technology, and pharmaceuticals, united by the mission to deliver better drugs to patients faster. Valo is committed to hiring diverse talent, fostering growth and development, and creating an inclusive environment where a variety of experiences, backgrounds, and voices contribute to our success. We aim to be a catalyst for the pharmaceutical industry, driving its digital transformation.

About the Role

Join our expanding in vitro modeling team as a Data Scientist, contributing to our advancements in data science, tissue engineering, and drug discovery. In this role, you will leverage your skills and experience to enhance the engineering of human tissue models, with a specific focus on cardiac and skeletal muscle models.

You will be an integral part of a team responsible for developing and constructing computational models, engineered tissue assays, statistical models, and machine learning-based tools for application across our drug discovery pipeline. A key objective will be optimizing our in vitro analysis platforms and experimentation processes.

Successful candidates will collaborate with a diverse group of scientists, engineers, and domain experts, transcending traditional industry boundaries to build powerful computational tools that advance the discovery and development of new medicines.

What you’ll do

• Collaborate with biologists and computational scientists to visualize, preprocess, and analyze datasets generated from human tissue models and bioengineering experiments.
• Create clear and informative data visualizations and statistical summaries to communicate findings to both technical and non-technical colleagues, including collaborative design and development of user interfaces.
• Develop predictive models and algorithms to identify factors influencing the development, manufacturing, and use of tissue models.
• Work with scientists and engineers to optimize experimental conditions and model in-vitro phenotypic responses to chemical and genetic perturbations, aiming to better understand complex biological systems and identify optimal drug candidates.
• Build models using large and diverse datasets to explain experimental variability and guide scientists on optimizing experiments and engineered tissue production through multivariate analyses, time series data processing, and other statistical and machine learning modeling techniques.

What you bring

• 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 (e.g., computational biology, bioengineering, biostatistics).
• A strong background in data processing and analysis.
• Familiarity with statistical methods and machine learning techniques and tools, including neural networks, generative models, ensemble learning, regression, classification, and regularization.
• Proficiency in Python and experience with data analysis libraries such as Pandas, NumPy, SciPy, Scikit-learn, and TensorFlow/PyTorch.
• Familiarity with version control systems for code, such as Gitlab or Github.
• Familiarity with bioengineering.