"Alerted.org

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.

An individual in this position is responsible for advanced technical bioprocess data science and batch performance improvements that add continuous value to the business operations. The incumbent’s influence can have a significant impact on the harvested value in reductions of cost of goods sold, favorable material variances, real-time process visualizations and through advancing industrial data science/statistics initiatives.

The incumbent must:

- Balance and prioritize project work according to business objectives. Balance multiple competing global and regional projects of varying complexity and prioritize project work within the group according to business objectives.

- Interact with counterparts in other divisions and regions.

- Ensure work is compliant with applicable procedures and requirements which vary by geographic region and agency.

The incumbent will interface with multiple Global Supply functions including IT Operations & Laboratories, IT Enterprise Data Services, Global Manufacturing Science and Technology, Global Facilities Engineering, Local Automation Engineering, Quality Control, and Quality Assurance, and Global Supply Leadership Teams. The incumbent will also represent the department and the company to external bodies including industry groups, and when necessary regulatory bodies.

Incumbent will participate on project teams, independently representing MSAT Data Analytics group perspectives. They will help to guide Data Management and Data Analytics positions, negotiate with members of other functions to influence study design, ensure compliance, and accurately interpret and report statistical principles and analysis results; will also contribute computer science expertise in other areas as Company business needs require.

Duties & Responsibilities

Guides the organization on strategy of advanced manufacturing analytics, and artificial intelligence (AI)/data science capabilities.

Designs and builds advanced hybrid and mechanistic process models, discovering insights and identifying opportunities using statistical and algorithmic methods (Machine Learning – E.g. PCA, PLS, OPLS) and industrial data science techniques.

+ As a critical thought leader in IT/OT convergence as it related to suitable data acquisition, data management, and data analysis; Identifies and resolves causes of poor data quality management, implements solutions and communicates findings to employees, management, and stakeholders.

+ Collaborates with Business Process owners and Data Stewards to develop methods for synchronizing data entering company systems.

+ Models the behaviors of championing data as an asset.

+ Works together with IT developers for the continuous improvement and maintenance of back-end database and reporting/analytics data exchange.

+ Drives and develops new ideas from the team to foster improvements through innovation.

+ Performs ongoing data analysis to develop a deep understanding of the impact on data with continuous improvement ontologies for business unit dynamics.

+ Examines patterns in the data and coordinate with business unit to define opportunities for deep-dive analyses.

+ Develops and implements a process for cross-checking validity of data pulls made by other members of the Global Manufacturing Science and Technology.

+ Clearly communicate 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.

+ Maintain cutting edge industrial knowledge including a demonstrated ability to interpret and adapt primary literature, trade forums, and user meetings evaluating and when profitable, adapting new/emerging technologies to ongoing MSAT projects to enhance Global MSAT Data Analytics Product Groups.

+ Prepare and deliver clear and concise well-organized content summaries to Data Analytics department head, global steering committees, MSAT forums, and technology boards. Effective communications and reporting.

+ Aligned performance feedback from critical stakeholders across the IT, GBS, GFE, Digital Operations, Global Supply Leaders, MSAT Networks Leads, and Site Leadership Teams.

+ Quality, quantity, and clarity of written and oral communications in a variety of formats. Confidence in results and skill.

+ Discern literature and advancing technology for innovative and collaborative technology to augment value stream analytics. Deliver summary and presentation to MSAT Leadership Teams.

+ Comply with company SOPs and relevant regulatory guidances at national and international levels. Act at all times within industry, company, and data management standards and ethics Apply solid understanding of relevant regulations governing the Animal Health industry. Lead in applying relevant regulations governing the Animal Health Industry, and exhibit excellent communication skills in working with regulatory agencies.

Requirements

Data Scientist IV

+ Master's in data science discipline or related degree with a minimum of eight (8) years industrial experience in Data Science, Predictive Analytics, or Cognitive Analytics OR Bachelor's degree in data science discipline or related degree with a minimum of ten (10) years of industrial experience in various data science disciplines.

+ Statistics, Computer Science, Data Science certifications in a industrial quantitative performance disciplines preferred.

+ Machine/Deep Learning, CRISP-DM, and Real-time MVDA certifications preferred.

Sr. Scientist

+ Bachelor's degree in Data Science, Statistics, Computer Science or equivalent field.

+ In addition to bachelor's degree, a minimum of seven (7) years of experience in data science, machine learning and/or MLOPs Engineering in regulated organization or similar organization. Experience must be inclusive of a minimum of three (3) years of project leadership involving program oversight for implementation of advanced analytics tools in relevant industry.

+ Expertise in SIMCA and SIMCA-online or equivalent, Seeq, JMP, R, Python, data mining and associated advanced data science tools tools, especially R and Python, AI Deep Learning, Large Language Modeling.

+ Expert in Microsoft SQL Server and relational databases.

+ Experience in Aveva PI platforms using Asset Framework and Event Frame data integrations.

+ Ability to liaison with Information Technology to ensure that the proper Extract, Transform, and Load (ETL) and database architecture is in place to fulfill MSAT needs.

+ Demonstrated expertise in systems and processes, creating and executing algorithms and distilling the solutions for a business audience, process improvement, preferably within the Pharmaceutical Industry.

+ Demonstrated understanding and ability to apply principles, concepts, practices, and standards including knowledge and use of Animal Health or Pharma data and working knowledge of industry practices.

+ Demonstrated ability to communicate ideas, facts, and technical information clearly and concisely to senior management, as well as other internal customers both verbally and written.

+ Excellent communication skills and ability to work with other disciplines.

+ Demonstrated ability to effectively manage multiple priorities.

+ Ability to lead a team or work independently with a high degree of accuracy and attention to detail in the fast-paced environment.

+ Sharp analytical abilities and proven statistics skills.

+ Models willingness to learn and stay up to date, as well as train others on data science related topics.

+ Exceptional organization and analytical skills, to critically evaluate information gathered from multiple sources, reconcile conflicts, decompose high-level information into details, abstract up from low-level information to a more general understanding, distinguish presented user requests from the underlying true needs, and distinguish solution ideas from requirements.

+ Comprehensive knowledge of database tools (Microsoft SQL Server, Aveva PI, Excel) to extract and manipulate large, complex datasets.

+ Data mining technical knowledge and skills including decision trees, multivariate analysis, segmentation modeling, factor analysis, regression analysis, forecasting, and machine learning.

+ Intellectual curiosity and commitment to teaching data analytics concepts to others in the organization or on team.

Desired Skills, Experience and Abilities

**Additional Requirements** :

+ Strong intrinsic appetite to develop technical skills.

+ Fluency in English required – fluency in French, Spanish, and German to support the interactions with other BI Network sites and stakeholders are preferred.

+ Willingness to travel domestically and internationally.

+ Demonstrated international/intercultural technical collaboration.

+ Demonstrated ability to identify and analyze problems, evaluate alternatives, and implement effective solutions.

+ Ability to work independently with a high degree of accuracy and attention to detail in the fast-paced environment.

+ Sharp analytical abilities and proven statistics skills.

**Eligibility Requirements** :

+ Must be legally authorized to work in the United States without restriction.

+ Must be willing to take a drug test and post-offer physical (if required).

+ Must be 18 years of age or older.

All qualified applicants will receive consideration for employment without regard to a person’s actual or perceived race, including natural hairstyles, hair texture and protective hairstyles; color; creed; religion; national origin; age; ancestry; citizenship status, marital status; gender, gender identity or expression; sexual orientation, mental, physical or intellectual disability, veteran status; pregnancy, childbirth or related medical condition; genetic information (including the refusal to submit to genetic testing) or any other class or characteristic protected by applicable law.