לצערנו המשרה כבר לא בתוקף

Data Science Intern, R&D

ללא נסיון |
משרה מלאה
| 04/03/2021
תיאור משרה

Advanced Analytics & Artificial Intelligence student is responsible to research, design, and deliver Analytic & Machine Learning solutions across Teva's pipeline. The AAAI student will be working on impacting drug discovery, development, precision diagnostics, prognosis, and personalized treatment through the following initiatives:

Smartening clinical trials - integrating wearable devices and mHealth
Healthcare informatics
Real world evidence and cognitive computing
Imaging
Voice analytics


Major Duties & Responsibilities:

Apply advanced machine learning expertise to research, design and develop novel data mining algorithms to identify biologically and clinically meaningful insights from diverse data sources
Be responsible for translating high-level requirements and business goals to robust and scalable solutions
Integrate data with the goal of discovering meaningful and actionable insights for fact-based decisions
Keep current with technology advances and competitive landscape in the digital health industry
Interpret and communicate the insights and findings from analysis to different stakeholders

דרישות התפקיד

M.Sc. \ Ph.D. student in Machine Learning, Electrical Engineering, Biomedical Engineering, Statistics or equivalent
Hands on experience with SQL
Working knowledge of scripting and programming languages relevant for advanced analytics such as Python, R, and Java
Ability to solve complex problems using creative ideas, state-of-the-art tools and best engineering practice
Proven track record in data mining, exploration and algorithmic model development, including predictive analytics
Expert knowledge and theoretical understanding of Big Data, pattern recognition, and machine learning; Knowledge and experience in Deep Learning is an advantage
Excellent written and verbal communication skills, in both English and Hebrew
Applied technical experience in advanced analytics, visualization and computational modeling, big data (Hadoop/Spark, AWS), search and various data integration tools is an advantage
Clinical, Pharmaceutical and Biological knowledge is an advantage