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Teva Associate Director Data Science US 
United States, Pennsylvania, East Bradford Township 
861953455

02.04.2024

The candidate is expected to have a deep knowledge in the field of Machine Learning, Advanced Analytics & Big Data, hands-on experience in algorithmic development and in deployment of solutions, and capability to initiate activities and work both individually and as a team member. Additionally, they should process significant experience in applying AI/ML approaches to optimize clinical trial activities, including patient recruitment, site selection, trial design, data collection and analysis. This role requires a strong understanding of the intersection between AI/ML technology and clinical operations, and the ability to innovate and implement solutions that enhance trial efficiency and effectiveness.

minimal

Remote (in the US, Eastern time zone preferred) - OR - On-Site in Israel

How you’ll spend your day
  • Develop algorithms and software solutions that integrate and evaluate large datasets from multiple disparate sources, and collaboratively identify biologically and clinically meaningful insights from large data and metadata sources
  • Lead and execute initiatives to apply AI and machine learning approaches to accelerate clinical trials, the areas of focus include patient recruitment, site selection, patient compliance and drop off etc.
  • Interpret and effectively communicate insights and findings to product, service and business managers with great attention to detail & accuracy
  • Proactively seek for new opportunities, ask the right questions, prioritize and translate the business requirements into a data science problem and solution
  • Expand applications across existing and novel Analytics & Big Data domains, including structured and unstructured data, wearables, social media, free text, videos, and digital applications
  • Interact in a multidisciplinary environment with internal and external stakeholders, collaborating with other members of a project team to meet scientific and technical goals
  • Keep current with technology advances and competitive landscape in the digital health industry
Your experience and qualifications
  • Master's degree in Data Science, Machine Learning, Electrical Engineering, Biomedical Engineering, or equivalent from an accredited college or university. (PhD preferred.)
  • Minimum of 2 years of applied technical experience in machine learning, advanced analytics, and algorithmic model development, including predictive analytics and deep learning.
  • Understanding of clinical trial processes, protocols, and operational challenges
  • Experience working with clinical trial data, electronic health records (EHRs), or real-world data (RWD) and applying AI/ML approaches to improve clinical trial design, patient recruitment, site and patient selection etc.
  • Good knowledge and theoretical understanding of Big Data, pattern recognition, and machine learning
  • Working experience with relevant scripting and programming languages such as Python, R, Java – especially with data related libraries; Hands on experience with SQL
  • Strong business orientation and problem-solving skills with great attention to details; Ability to solve complex problems using creative ideas, state-of-the-art tools and best engineering practice
  • Domain knowledge and working experience in healthcare and life science is an advantage
  • Publication record in Machine Learning is an advantage; Publication record in clinical studies is an advantage
  • Excellent written and verbal communication skills in English
Reports To

Head of Advanced Analytics and Artificial Intelligence

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