Data Scientist

Job Description

Core technologies and methodologies: C, C++, Qt, Python, Embedded Systems, Machine Learning, Deep Learning, Artificial Intelligence.

• MS in Math, Statistics, or Computer Science
• Knowledge of fundamental descriptive and inferential statistics models.
• Strong computational/programming skills: proficient in programming with R, Python, SQL or equivalent, knowledge of a variety of commercial computational packages, familiar with Linux, AWS, cloud computing and high performance computing environment.
• Knowledge of data visualization tools such as Spotfire or Tableau.
• Good team player with demonstrated ability to build effective working relationships within and across sites with customers and partners.
• The flexibility to balance many projects and customers simultaneously.
• The ability to be independent and learn new skills quickly.
• Demonstrated ability to independently develop and deploy statistical / computation applets using Python and R.
• Exceptional oral and written communication skills
• Coursework in a scientific discipline (chemistry, biology, engineering).
• Prior experience working in pharmaceutical research and development.
• Experience in ML/AI development and deployment.
• Experience in text mining.
• Hands-on experience applying a wide variety of statistical machine learning techniques to real world problems spanning analysis, predictive modeling and optimization on structured and unstructured data
• Experience using tools such as Python, R, or equivalent for statistical modeling of large data sets
• Well-developed written and oral communication skills with ability to present complex statistical concepts to non-analytical stakeholders (Excel, Word and PowerPoint are a must)
• Software engineering experience in C/C++/C#/Java/Scala or similar object oriented or functional languages is highly regarded but not a prerequisite
• Excellent SQL (and or similar language Ex: Python) and data analysis skills
• Experience working with large data volumes and data complexity
• Experience with quality assurance activities and test case development
• Strong interpersonal and leadership skills
• Business acumen, for example, in understanding the problem, formulating hypotheses and testing conclusions to determine appropriate methods to influence strategic choices through data.