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 Data Scientist IV, Manufacturing Science and Technology is responsible for the delivery of successful data science projects. The incumbent will be the "go to" expert for data science within Manufacturing Science and Technology, for BIAH products and processes throughout the product lifecycle. This role will facilitate, distill and integrate data science information into the technical body of knowledge for BIAH products and processes. The position holder will explore data analytics innovations to support future definition of manufacturing platforms & processes.
The Senior Data Scientist, MSAT executes data science and advanced analytics projects across the company with the purpose of solving business problems by applying advanced industrial data science methods including real-time multivariate process modeling and predictions, machine learning, artificial intelligence, causal inference, advanced statistics, natural language processing and other related techniques. The incumbent will develop relationships with business partners to enhance understanding of business issues and create value for the organization. Executing data mining and analytics projects with high potential return and inventing/iterating novel solutions to challenging data-related problems will be the primary focus of the Data Scientist.
The SR Data Scientist, MSAT utilizes experience to manage complex projects including external support and develops, mentors or leads a team of more junior colleagues. Critical to ensure that the company utilizes a wide array of reliable data analysis techniques to deliver data-driven Operations Intelligence inside the Global Manufacturing Science and Technology organization (MSAT).
Specific areas of focus include delivering and optimizing solutions for data mining, aligning data processing and predictive algorithms with business goals, and transforming data into knowledgeable information.
Duties & Responsibilities - Data Scientist IV
Be the "go to" expert for data science within Manufacturing Science and Technology, for BIAH products and processes throughout product/process lifecycle:
Uses data scientific techniques to uncover processes & correlations to expand & improve the body of knowledge for BIAH products & technology
Delivers optimized solutions for data mining, aligning data processing, predictive analysis and transform data into knowledgeable and understandable information.
Partners with business units to develop dashboards and applications utilizing data for smart decision making.
Promotes collaboration & knowledge exchange with other data science teams within and outside the organization.
Provides thought leadership, research best practices, conduct experiments, & partner with industry leaders.
Facilitates, distills, and integrates data science information into the technical body of knowledge for BIAH products and processes:
Uses data scientific techniques to uncover processes & correlations that expand and improve the body of knowledge for BIAH products & technology.
Leads exchange and advocate for continual improved use of data across global and local Manufacturing Science and Technology teams.
Identifies and resolves causes of poor data quality management, implements solutions & communicates findings.
Actively supports all aspects of the BI data governance standards and programs.
Continually develops and maintains an appropriate individual level of theoretical and practical expertise to respond to the needs of BIAH.
Explore data analytics innovation to support future definition of manufacturing platforms & processes:
Actively networks on a regular basis with internal and external partners.
Autonomously seeks out new ways of using & connecting data for use in existing or new manufacturing processes.
Autonomously researches and recommends future-oriented platforms for analytics enablement efforts.
As needed, deliver successful data science projects:
Understands manufacturing / supply problems and design end-to-end data science use cases.
Collaborates across Global Supply to understand data, IT and business constraints
Prioritizes, scopes, & measures relevant Key Performance Indicators/Objectives & Key Results for success.
Collaborates with Global / Local Manufacturing Science and Technology, Supply Chain, and the Supply Network to deploy scalable solutions.
Establishes data operational best practices and maintain all compliance requirements
Establishes the monitoring of data science models in production.
Uses agile approach to initiatives and launches.
Ensures and measures customer satisfaction.
Requirements - Data Scientist IV
Bachelor's degree in data science discipline or related degree with minimum of five (5) years of industrial experience in various data science disciplines (Data Science, Computer Science/Business Intelligence, Predictive Analytics, Cognitive Analytics) required. Statistics, Computer Science, Data Science certifications in an industrial quantitative performance discipline preferred.
Experienced in structuring data sets from unstructured data or big data (MapReduce approaches, HDFS, Hadoop architectures, Pig, Spark).
Expertise in data engineering and @contextualization of batch and attribute data by managing pharmaceutical object-oriented programmatic methodologies; specifically, PostgreSQL, Kubernetes, WebAPI, SQL, C#, GO, React, .Net, Java, GraphDB/GraphQL, InfluxDB, MongoDB, OSI PI, R, Python, SAS JMP, Spotfire/Tableau, SASEntreprise, Inmation/VisualKPI, SIMCA, SIMCA-online, and Grafana.
Strong expertise in relevant methods and skills such as machine learning, advanced statistics, algebra, data visualization, artificial intelligence, natural language processing, classification methods, feature extraction, dimensionality reduction, data handling algorithms, regression methods, time-series analysis, predictive modeling, causal inference methods, Bayesian networks, Markov random fields, text analysis, etc.
Experienced in handling data bases including ability to run queries.
Basic understanding of web scraping and text processing.
Sound knowledge in scripting languages such as PHP, Perl, Bash.
Well-developed understanding of data hygiene as well as data enrichment.
Machine/Deep Learning, CRISP-DM, and Real-time MVDA certifications preferred.
Demonstrated expertise in the time-series batch execution systems, ISA-88 batch execution sequencing and @contextualization, creating and executing advanced pharmaceutical batch modeling algorithms, interpreting results, distilling solutions and reports for a business stakeholders that facilitate process awareness and improvements in predictability of critical parameters and quality attributes.
Demonstrated expertise in project and change management within the Pharmaceutical Industry
Ability to rapidly develop analytical problem-solving approaches to complex problems, including external constraints such as resource limitations, feasibility topics, consumption by business, change management aspects, etc.
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 clearly and concisely communicate ideas, facts, and technical information to senior management, as well as internal customers both verbally and written.
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.
Requirements - Senior Data Scientist, MSAT
Bachelor's degree in Data Science, Statistics, Computer Science or equivalent field required.
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, 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.
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.
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.
Intellectual curiosity and commitment to teaching data analytics concepts to others in the organization or on team.
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.
