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 the Data Scientist IV, Manufacturing Science and Technology role is to deliver 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 Data Scientist IV, Manufacturing Science and Technology will explore data analytics innovations to support future definition of manufacturing platforms & processes.
Duties & Responsibilities
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.
Explores 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, delivers successful data science projects:
Understands manufacturing / supply problems and designs 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 & measures customer satisfaction.
Requirements
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 (Data Science, Computer Science/Business Intelligence, Predictive Analytics, Cognitive Analytics).
Statistics, Computer Science, Data Science certifications in a industrial quantitative performance disciplines preferred.
Machine/Deep Learning, CRISP-DM, and Real-time MVDA certifications 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.
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.
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.
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.
Well-developed understanding of data hygiene as well as data enrichment.
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.
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.
