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Data Scientist
New York
$75 - $85
+ Life Science Analytics
ContractNew York
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Data Scientist
12-Month Contract
$75-$85/hr
Are you a skilled Machine Learning Engineer with a passion for cutting-edge technologies? Join this innovative team where you can demonstrate your expertise in machine learning techniques, probabilistic reasoning, and optimization.
Key Responsibilities:
- Create interpretable models and implement advanced algorithms for production use.
- Demonstrate hands-on experience in supervised and unsupervised machine learning techniques.
- Exhibit strong skills in Python, R, Keras, TensorFlow, and .NET integration.
- Act as a key contributor throughout all phases of the design and development lifecycle for analytic applications, utilizing various technology platforms.
- Develop and implement analytic solutions on Amazon or Azure cloud platforms, working with a variety of databases including relational, in-memory, NoSQL, document, and graph databases.
- Utilize strong analytical skills to translate complex business requirements into effective architectural solutions.
- Design and implement data pipelines for both batch and real-time analytical model consumption.
- Demonstrate experience with APIs, web services, dimensional data modeling, and data transformation.
- Show proficiency in SQL with a broad understanding of language constructs.
Requirements:
- Familiarity with data integration, ETL, and ELT tools
- Experience with Power BI, particularly in integrating machine learning capabilities.
- Hands-on experience in Azure environments, including Azure Machine Learning.
- Understanding of DevOps practices, CI/CD processes, and agile methodologies, including tools like Git and Azure DevOps.
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Machine Learning Engineer (Life Sciences)
Boston
$90 - $100
+ Life Science Analytics
ContractBoston, Massachusetts
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Machine Learning Engineer (Life Sciences)
12-Month Contract
Hybrid in Boston, MA
We are working with a well-established Life Sciences company whose mission is to transform the lives of people with serious diseases. Their team is seeking an MLE to build and scale the machine learning infrastructure behind their next-generation therapeutic discovery platforms. You’ll work at the intersection of cutting-edge ML and translational science to accelerate the development of life-changing treatments for patients worldwide.
Responsibilities:
- Architect and implement ML systems that support therapeutic discovery platforms, with a focus on performance, scalability, and reliability in a clinical research environment.
- Analyze and optimize machine learning workflows by identifying bottlenecks and developing solutions to improve efficiency and throughput.
- Establish MLOps best practices across the organization, including experiment tracking, model versioning, and automated deployment pipelines.
- Lead the integration of ML systems with broader software and data infrastructure to enable seamless data flow and interoperability across the discovery pipeline.
Requirements:
- Demonstrated experience designing, building, and optimizing end-to-end machine learning systems, particularly for biological or clinical research data.
- Deep understanding of machine learning techniques, including experience applying deep learning to complex, high-dimensional biological datasets.
- Strong domain knowledge in areas such as cell biology, genetics, immunology, or related fields within life sciences or biomedical research.
- Advanced proficiency in Python and experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn.
- Proven track record of implementing robust data infrastructure and tooling to support scalable ML workflows in a scientific or healthcare setting.
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