YOUR TASKS ANDRESPONSIBILITIES
- Lead analytical projects, including business question development, generating relevant hypothesis and scoping in the area of Pharmaceutical Product Supply (API) and drive the definition, design, implementation and validation of cutting-edge advanced data analytic algorithms and models
- Develop and train members of the Pharmaceutical Product Supply (API) Digital Transformation Team and maintain awareness of state-of-the-art technologies of advanced data analytics and artificial intelligence platforms as well as transforming data science prototypes to end to end solutions
- Perform complex simulation, modelling and machine learning algorithms, integrate multi-layered data models from process related data sources like quality systems, process control systems, etc., process optimization and root cause analysis
- Analyze diverse data sources to achieve targeted outcomes by leveraging complex statistical and predictive modeling concepts, machine-learning approaches, clustering and classification techniques
- Build up and continuously update relevant process knowledge and to contribute to the development of new innovative analytical solutions, proactively identify opportunities and solve challenging production and quality process issues with a variety of data tools in fast-paced cloud environments and work closely with product supply production and quality departments to develop digital strategies to improve product quality and performance outcomes
- Analyze the data structure/data flow and develop complex analytical models of product supply processes to create opportunities by identifying bottlenecks and pain points to improve efficiency and decision making, including KPIs to determine success
- Develop dashboards for real-time monitoring and trending of production processes with the use of statistical control limits based on the standard deviation. Utilize advanced analytics for reflection and recommendations in case of adapting threshold limits, alert limits or action limits
- Collaborate with corporate IT- and Engineering functions to understand the implications of respective architectures on cooperate data analytics and data integration/cloud platforms and maximize the value of data
WHO YOU ARE
- Post-graduate degree (Master's or Ph.D.) in Informatics, Bioinformatics, Physics, Mathematics, Statistics or equivalent education
- Several years of professional experience in a GxP related Life Sciences Industry, ideally in Pharmaceutical Product Supply, where big data analytics already play a significant role
- Highly experienced in a big data environment (structured and unstructured data sources), using advanced analytics, artificial intelligence, deep learning frameworks and machine learning algorithms
- Solid understanding in statistical performance data, trend analysis to determine process anomalies and a broad understanding in a variety of data environments, like Hadoop HDFS, Oracle, Microsoft, Mongo, etc. as well as excellent coding knowledge in scripting languages like Python, R, etc.
- Strong business acumen and able to collaborate closely with business teams as a sparring partner to identify high-impact opportunities by leveraging our extensive data assets
- Passion for team-work with excellent interpersonal and communication skills as well as excellent presentation and communication skills to interact within a highly complex environments
- High ability to solve problems and to structure and simplify complex scenarios and implement and lead digital transformation change
- Fluent in English and German, both written and spoken
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