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Join AiDOOS: Empower Your Micro-Company Today!

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  • Form micro-companies around niche technologies
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  • cale up your team to take on bigger projects
Remote Principal Data Scientist
Budget: $0.00

Technologies: SQL, Data Manipulation, Data Visualization, Hadoop, Machine Learning Algorithms, Python, R, Scala, Spark, Statistical Modeling

Duration: 12

Seeking a Principal Data Scientist to work remotely and focus on analyzing and synthesizing data into results that are easily understandable. This position involves leading the creation of data-driven solutions to solve business challenges and improve business processes.

The Data Scientist will design data modeling, algorithms, processes, and predictive models while working closely with stakeholders to establish an understanding of their goals and initiatives.

The successful candidate for this role should be an expert in programming languages such as Python, R, SQL, and Scala, as well as have proficiency in data manipulation, data visualization, machine learning algorithms, and statistical modeling.

The candidate should also possess experience with big data technologies such as Hadoop, Spark, and Kafka, as well as familiarity with cloud services such as AWS and Azure.

In terms of education and professional experience, the ideal candidate should have a Master's degree or PhD in Data Science, Computer Science, Statistics, Engineering, Mathematics, or a related field.

A minimum of 7 years of experience in data science or analytics is also required, with a proven track record in leading and delivering data-driven projects and solutions, as well as demonstrated experience in managing large datasets and conducting complex quantitative analyses.

The mission of the Center for Devices and Radiological Health (CDRH) is to protect and promote public health. CDRH assures patients and providers have timely and continued access to safe, effective, and high-quality medical devices and safe radiation-emitting products. Rackner will be working with CDRH to help develop a comprehensive multi-faceted system to streamline FDAs capability to use state-of-the-art approaches to generate and evaluate clinical evidence for regulatory decision-making, including advanced artificial intelligence and machine learning (AI/ML).