Sr Data Scientist - L3

What you do?  Use a combination of local and cloud tools to analyse, cleanse and transform different types of data and content for consumption by AI and machine learning models.  Use the most appropriate data modelling / machine learning principles and tools to design, explore and build scalable data solutions, potentially from source systems through to the presentation layer.  Where required, develop data and software solutions to deliver a robust and automated deployment of AI/ML services for everyday business use.  Collaborate with subject matter experts to understand the operational challenges and goals and to then explore, design and build appropriate data solutions to meet those goals and alleviate the business challenge.  Collaborate with software engineers and other IT professionals to understand the capabilities and constraints around security, data governance and technology infrastructure to ensure that AI solutions are scalable, automatable, cost efficient and secure and that they comply with data policies and regulations.  Work to differentiate ICON from competitors by exploring and developing solutions that drive meaningful outcomes for customers.  Monitor and be aware of trends in technology, data sciences and business practice in the pharmaceutical industry, and provide advice and recommendations on emerging AI/ML trends and applications.  Work to deliver maximum customer value for minimum cost.  Undertake other reasonably related duties as may be assigned from time to time.  Recognize, exemplify and adhere to ICONs values which centre around our commitment to people, clients and performance.  As a member of staff, the employee is expected to embrace and contribute to our culture of process improvement with a focus on streamlining our processes adding value to our business and meeting client needs. What you need?  Degree in a relevant IT or natural sciences discipline.  6+ years of experience in the use of machine learning, artificial neural networks, natural language processing and robotic process automation.  Ability to translate a business problem into an analytical problem that can be solved with data and machine learning.  Good knowledge of statistics and statistical analysis.  Experience with a wide range of data storage technologies and architectures, including data warehouses, data lakes, graph databases, NoSQL and clustering and experience working with structured data, semi-structured data and unstructured data.  Advanced skills in data wrangling, analysis and visualization.  Mature software engineering skills, including primary code development, code optimization and workflow and deployment scripting.  Good knowledge of cloud services, including serverless computing services and machine learning tools