Staff Data Scientist
Mission Lane147,000 - 179,000 USD/year
- Full Time
- Senior (5 to 8 years)
Not SpecifiedCompensation
Junior (1 to 2 years), Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Pharmaceuticals, Biotechnology, Healthcare, AI & Machine LearningIndustries
Requirements
Candidates should possess a degree in a quantitative field with a minimum of 7 years of post-degree experience or equivalent, or 5 years with an MS, or 3 years with a PhD. They require 3+ years of experience in machine learning, including supervised and unsupervised learning, dimensionality reduction, clustering, and model selection, along with 2+ years of experience working with electronic health records (EHRs). Proficiency in Python (5+ years) and experience with ML packages such as scikit-learn, statsmodels, and scipy are essential, as is 3+ years of experience with MLOps methodology, including workflow orchestration, experiment tracking, containerization, and reproducible research. Furthermore, candidates must have 2+ years of experience with large-scale data analytics engines like Spark or Dask and working in cloud environments such as AWS, and 3+ years of experience with collaborative software development using source control management and CI/CD.
Responsibilities
The Staff Data Scientist, Machine Learning will propose, design, and develop ML approaches on high-dimensional electronic health records and omics data using Valo’s platform. They will also design, develop, and support ML pipelines and dashboards to enable users to solve scientific problems, develop well-designed and documented software packages, collaborate with cross-functional teams to derive user requirements and ensure alignment, and actively participate in code, design, and analysis reviews.
Skills
Python
scikit-learn
statsmodels
scipy
MLlib
Airflow
Prefect
MLflow
Docker
git
unit testing
CI/CD
Spark
Dask
AWS
Electronic Health Records
Machine Learning
Data Science
Big Data
Cloud Computing
Model Development
Model Explainability
Model Selection
Feature Selection
Clustering
Dimensionality Reduction
Supervised Learning
Unsupervised Learning
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.
Key Metrics
Boston, MassachusettsHeadquarters
2019Year Founded
$474.2MTotal Funding
LATE_VCCompany Stage
AI & Machine Learning, BiotechnologyIndustries
51-200Employees