Senior Data Scientist

with wide-ranging analytics experience to work within a diverse operations business which includes Supply Chain, Manufacturing, Quality, Purchasing and Science & Technology.
- will build and oversee the building of predictive/prescriptive models using statistical and machine-learning methodologies.
- will also ensure end-to-end delivery of assigned data science applications, studies and POCs overseeing project teams of junior data scientists and data analysts.

 
Role

• Role is expected to quickly assess new opportunities (AI/ML techniques, technology, etc.) and present these within the current and future state of requirements, risk, and cost-effectiveness.
• Perform requirements discovery, determine feasibility of various approaches, devise experimental approaches to test assumptions and devise solutions which incorporate non-functional requirements such as scalability, interpretability, and maintainability.
• Drive one or more key internal initiatives such as cross-functional GenAI development, data science platform evolution or operations-wide MLOps / governance / methodology / SLC updates appropriate for AI/ML in addition to planned and ad hoc functional initiatives.

Requirements:

• Expert knowledge of statistical and machine learning methods, with expertise in modeling and business analytics
• Data Science tools like Knime, Dataiku, AWS SageMaker, statistical languages, and packages, e.g., R, Python, Julia, SAS, data visualization tools and techniques, e.g., Tableau, ggplot, matplotlib, R/Shiny, Qlik, data manipulation tools such as SQL, Spark, PySpark and Hive, cloud environments like Azure and AWS, deep learning tools such as Tensorflow, Keras and PyTorch 
• Expertise in designing and developing processes and systems to consolidate and analyze data. Considerations include variety (structured, unstructured), volume (includes big data), data quality (cleaning and validation of the data) and velocity (batch, stream).
• Expertise in processes / procedures for missing data analysis, data quality, master data management and good preparation practices for modeling.
• Expertise in story-telling with data and communicating complex topics to audiences of all levels
• Able to drive internal learning through journal clubs, internal data science education sessions and continuously deepen the team knowledge in data science practice and research.
• Able to communicate effectively to an executive level audience.

Required

• Undergraduate with 7 years of experience, master’s degree with 6 years of experience, or PhD in a related quantitative field with 2 years of experience, in a non-academic setting
•  Data Science/Statistics/Predictive analytics or similar. For advanced degree holders, preference is for quantitative or engineering undergraduates such as chemistry/chemical engineering, mathematics, other industrial / engineering degrees.
• Experience in full life-cycle and evolution of complex data science applications including Agile Project management processes
• Self-learner able to quickly become effective in new tools, concepts, and academic findings relevant to OBI/stakeholder needs.

• Experience in Quality, Manufacturing or Central Operations context in a large pharmaceutical environment including GxP systems and processes.
• Awareness or experience in key industry trends in related areas such as ‘Factory 4.0’ or ‘Smart Manufacturing’ in pharmaceutical manufacturing operations.
• Experience in technology transfer and innovation practices through consulting experience or through corporate roles supporting these practices.
• Experience in MLOps/SLC in Pharmaceutical operations.

Please email your resume or use this link to apply directly:

https://brainsworkgroup.catsone.com/careers/index.php?m=portal&a=details&jobOrderID=16414169
Or email: igork@brainsworkgroup.com
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keywords: science statistics predictive analytic quantitative pharma ML Ops/SLC