Principal/Sr. Principal Solutions Engineer

Description

As an employee of Boehringer Ingelheim, you will actively contribute to the discovery, development, and delivery of our products to our patients and customers. Our global presence provides opportunity for all employees to collaborate internationally, offering visibility and opportunity to directly contribute to the companies' success. We realize that our strength and competitive advantage lie with our people. We support our employees in several ways to foster a healthy working environment, meaningful work, mobility, networking, and work-life balance. Our competitive compensation and benefit programs reflect Boehringer Ingelheim's high regard for our employees. The basic purpose of this role is to autonomously lead full stack Data Analytics software configurations for global and regional Data Analytics Product Groups. The Sr. Principal Solutions Engineer, Data Analytics is responsible for continuous design, development, configuration and maintenance of parameterized contextualization schemes relative to Manufacturing Science and Technology data science requirements. This role leads collaboration among global business stakeholders and site leadership teams; including Global IT, and Global Engineering. The incumbent will participate in the Advanced Analytics Strategy Forums to drive enterprise data management and systems architectural requirements. The primary expectation of this role is to be a world class expert in Data Analytics Computer Science. This includes proficiency in full stack data management supporting pharmaceutical and bio-pharmaceutical data sciences/advanced analytics. The incumbent is expected to work independently and coordinate global efforts on clean structured data acquisitions, data transformations, and data integration efforts required to enable statistical modeling, visualization, reporting, and interpretation of results. This role will coordinate the preparation of Quality Risk Assurance based data integrity and validation reports with appropriate business acumen for stakeholder interpretations and qualifications. The Sr. Principal Solutions Engineer, Data Analytics will manage junior level Data Engineers to provide analysis-ready batch contextualized vector and attribute data to statisticians and data scientists for applications of generalized linear modeling, time-series multivariate statistics including Principal Components Analysis and Partial Least Squares, QC test method validations, ANOVA/means comparisons, and univariate and multivariate Statistical Process Control (SPC) methodologies. This position is expected to collaborate and represent Data Analytics best practices to promote a broad Analytical Engineering ecosystem that delivers financial business value. This role will identify and implement new commercial and open-source software technologies that support more effective and efficient data science user experiences across multiple sites and programs.

Duties & Responsibilities

Sr. Principal Solutions Engineer, Data Analytics

• Executes the duties of data management and software configurations for complex pharmaceutical batch analytics.
• Maintains a high level of business acumen and data science knowledge to ensure the fit, form, and function of data science software.
• Collaborates with Data Analytics management, team, and stakeholders, to set and achieve project goals.
• Assumes departmental responsibility for multiple projects; capable of working independently to deliver objectives in a timely manner and capable of compiling industry standard reports suitable for internal compliance and/or regulatory submission.
• For projects of diverse complexity, provides architectural configuration support for all process historians, ERP, LIMS, and Electronic Batch Systems.
• Identifies and implements new commercial and open-source software technologies that support more effective and efficient data science user experiences across multiple sites and programs.
• Conducts periodic review of LAN, WAN, Edge servers in regional data centers and software architectures relative to data transfer rates and create data flow latency summarizations to ensure optimum user experiences for data scientists and local users.
• Continuously ensures agile software and data management effectiveness to support standard and advanced data science programs and product groups.
• Receives feedback and adjusts program management effectiveness from Global MSAT, Strategic site stakeholders and leadership, IT Governance bodies, and Global Engineering.
• Clearly communicates all aspects of data management requirements and functionality relative to Advanced Analytics outcomes to a diverse group of global stakeholders at all levels and locations of the organization.
• Maintains cutting edge industrial knowledge including a demonstrated ability to interpret and adapt primary litera