• Identify valuable data sources and automate collection processes
• Undertake preprocessing of structured and unstructured data
• Analyze large amounts of information to discover trends and patterns
• Build predictive models and machine-learning algorithms
• Combine models through ensemble modeling
• Present information using data visualization techniques
• Propose solutions and strategies to business challenges
• Collaborate with engineering and product development teams

A. CORE COMPETENCIES

1. COMMUNICATION SKILL. Should have the ability to effectively communicate with others.
2. CRITICAL THINKING. Should have the ability to conceptualize, analyze, synthesize and evaluate varying information as a guide to a decision or action.
3. PROBLEM SOLVING and ANALYTICAL THINKING. Should have the ability to identify the root cause and to resolve issues.
4. ATTENTION TO DETAIL. Should have the ability to effectively accomplish a task by going through all relevant details and information.
5. TEAMWORK. Should have the ability to cooperate and use own skills in order to achieve a common goal.

B. TECHNICAL COMPETENCIES

1. Understanding of machine-learning and operations research
2. Knowledge of Python, R and SQL; familiarity with Scala, Java or C++ is an asset
3. Experience using business intelligence tools and data frameworks

 C. QUALIFICATIONS:

1. Graduate or Post Graduate Computer Science, Engineering or relevant field; graduate degree in Data Science or other quantitative field is preferred
2. At least 2-3 years of relevant experience
3. Proven experience as a Data Scientist or Data Analyst
4. Experience in data mining
5. Prior experience in pharmaceuticals / clinical laboratories processes and data will be good to have