Sr. Data Scientist
With operations in 35+ nations and ~27,000 employees worldwide, CSL is driven to develop and deliver a broad range of lifesaving therapies to treat disorders such as hemophilia and primary immune deficiencies, and vaccines to prevent influenza. Our therapies are also used in cardiac surgery, organ transplantation and burn treatment.
CSL is the parent company of CSL Behring and Seqirus. CSL Behring is a global leader in the protein biotherapeutics industry, focused on bringing to market biotherapies used to treat serious and often rare conditions. CSL Behring operates CSL Plasma, one of the world's largest collectors of human plasma, which is used to create CSL’s therapies. Seqirus is one of the largest influenza vaccine companies in the world and is a transcontinental partner in pandemic preparedness and a major contributor to the prevention and control of influenza globally.
We invite you to take a look at the many career possibilities available around the globe and consider building your promising future at CSL by becoming a member of our team!
The purpose of the Senior Data Scientist (DS) position is to increase the efficiency & performance of CSL business operations and, concurrently, to increase patient access to CSL therapies.
Senior Data Scientists will accomplish these objectives by working closely with Subject Matter Experts (SMEs) to define operational areas to improve, data to be leveraged and business metrics to examine and analyze.
Senior Data Scientists will execute analytical projects that span the continuum of: descriptive, predictive and prescriptive analytical techniques. Senior Data Scientists will work with a wide range of internal and external data sources to analyze and examine areas of improvement across all CSL business units and functions.
DS responsibilities within each analytical project include: scope and define analytical projects in conjunction with SMEs across CSL; take the lead on writing, reviewing and managing to project charters for each analytical project; plan and develop analytics projects based on business and technical requirements; work with application developers to extract internal data relevant for analyses; define and cost relevant external data that may be used; build, test, and refine analytical models; update, upgrade and refresh analytical models; present results to the AA&AI team; present results to SMEs and their managers; recommend courses of action to improve business operations based on findings from analytical projects.
Senior Data Scientists work closely with SMEs in all business units across CSL and IT.
Senior Data Scientists should be inquisitive, challenging, and skilled in applying a wide range of analytical techniques to business and technical problems.
Senior Data Scientists will be supporting an innovation agenda with a goal of proposing practical solutions that improve CSL business processes by using relevant data, integrated in novel ways, coupled with analytics that provide continuous improvement to achieve world-class status in operations.
Main Responsibilities and Accountabilities:
- Collaborate with Subject Matter Experts (AA&AI Community of Practice (COP))
- Define and scope analytical projects in conjunction with SMEs across CSL
- Write, review and manage to project charters for each analytical project
- Plan and develop analytics projects based on business and technical requirements
- Work with SMEs to understand internal and external data required to achieve analytical project objectives
- Present milestone accomplishments to SMEs and their managers
- Revise project charters to ensure that business value is being delivered in line with expectations
- Manage project in conjunction with SMEs to ensure projects deliver on the business requirements
- Make recommendations for operational changes and improvements based on analytical findings
- Consult with SMEs and managers on implementing operational changes
- Design the technical, data and process elements of the project and project charter
- Translate business needs into the technical requirements for each project charter
- Work with application developers to extract internal data relevant for analyses
- Work with SMEs and external vendors to acquire relevant external data for analyses
- Develop and apply advanced analytical techniques & algorithms for analysis of large-scale, high-dimensional data across various business domains (Commercial, Engineering, Clinical, Manufacturing, Supply Chain, Pharmacovigilance, R&D, Legal, HR, etc.)
- Collaborate with teams at headquarters, manufacturing sites, commercial offices, Plasma offices and operations to elicit and understand their requirements and challenges and potential solutions
- Review project charters with SMEs, external vendors, IT and relevant stakeholders to gain buy in and agreement on project approach and execution
- Work as an actively contributing member of the Center of Excellence team (AA&AI COE)
- Stay abreast of industry developments in technology, analytics and competitive areas
- Stay current with latest research and technology ideas; share knowledge by clearly articulating results and ideas through papers, presentations to research staff, management, and key decision makers
- Share new knowledge with the COE members
- Review/test code written by other's for critical feedback
- Provide thorough and continuous documentation
- Skilled in data visualization and communication
- Evolve Pilots, PoCs and/or single site solutions to global enterprise solutions
- Work as an actively contributing member of the Community of Practice (AA&AI COP)
- Participate in the monthly Data Science calls
- Present at monthly Data Science call at least every other month
- Share new knowledge with the COP/SME members
- Help SME teams to hire data science and related talent
- Share hiring best practices and tools used in evaluating data science candidates
- Contribute to and present at annual Data Science Summit
- Develop and share analytical best practices
- Bring a fresh and unique perspective to analytical projects
- Use known techniques from other industries and apply those techniques to known challenges at CSL
- Use a broad ensemble of internal and external data in novel ways to develop insights that can improve operations
- Work with Business Development and Corporate Strategy to review and consider new partnerships to create new and impactful solutions
- Use open source and new techniques and technologies to develop new insights
- Continually improve technical, collaborative and (if desired) managerial skills
- Attend continuing education programs on analytical techniques and methods
- Attend outside events that will develop ideas, skills and professional network
- Find and take relevant external courses
- Look for projects that will stretch and improve skills and deepen/broaden the understanding of CSL operations
Position Qualifications and Experience Requirements:
- Degree Level:
- Ph.D. with at least 1 year experience, or
- M.S.with at least 4 years of non-academic work experience
- Major(s): Computer Science, Statistics, or Engineering
- At least 4 years of work experience, and at least 2 years of experience of working with Python, R and SQL/Hive
- Strong background in predictive analytics, machine learning and data mining
- Strong foundation in least 1 of the following data base languages: Pig, Hive, SQL,
- Strong foundation in least 1 of the following DS languages: Python, R
- Experience working with real-world, large-scale, and high-dimensional data sets
- Demonstrated ability to work both independently and within a team environment
- Strong analytical and problem solving skills and enthusiastic about learning new tools & technologies
- Excellent communication and documentation skills
- Hands-on experience with the Hadoop stack (Hadoop/Spark Paradigms)
- UX and UI design experiences is a plus
- Experience in the process or manufacturing industries are a plus
- Drive for results
- Functional / Technical skills
- Customer Focus
- Problem Solving
- Priority Setting
- Global Business Knowledge
- Business Acumen
- Presentation Skills
- Cultural Sensitivity
- English language fluency, additional language(s) is a plus