- Apply Data Science/Machine Learning approaches to establish relationships between material properties, manufacturing processes and product performance. Identify new product development or process improvement opportunities based on the insights.
- Build Natural Language Process (NLP) driven solutions from identifying business problems, collecting training dataset, analyzing data, modeling, to validating and delivering NLP models
- Collect unstructured and structured data from multiple sources and apply ETL (Extract, Transform and Load) techniques to develop propriety databases and build knowledge maps
- Collaborate with IT and Engineering functions on development of process simulation models (Digital Twins) for selected manufacturing processes
- Design, develop, and lead complex projects using analytics techniques.
- Translate conceptual ideas and research questions into data-driven analyses to allow informed decision-making and solution development.
- Communicate outcomes clearly and with effective data visualizations to team members and stakeholders of varying technical experience or familiarity with analytical methods
- Ideate and analyze large amounts of data to identify opportunities to advance Digital Transformation Strategy within the Innovation Group and propose new Digital Platforms
- Maintain a continuous education of cutting-edge statistical techniques and programming languages
- Have a passion and curiosity to work in research and development environment
- Can adapt to shifting priorities appropriately and help others operate with flexibility.
- Demonstrate a high degree of energy, self-motivation, personal commitment, and ownership.
- Offer new ideas, think "outside the box" and have an ability to explore multiple possibilities for tackling challenges to come up with best solutions.
- Learn continuously and stay up-to-date with current science trends.
- PhD with 0-2 years, Masters with 3-5+, or Bachelors with 5-10 years of relevant work experience in process modeling in a manufacturing and/or R&D environment. Degree in Engineering, Statistics, Applied Mathematics or Data Science preferred
- Track record of applying AI approaches in product formulation and/or process modeling
- Required experience with programming languages (e.g. R, Python, MATLAB.) and experience in NLP model development is a plus.
- Familiarity with ETL data engineering techniques using PySpark within Databricks/Snowflake preferred.
- Prior experience with implementing & training Deep Learning models (Pytorch, TensorFlow)
- Prior experience with training models on cloud infrastructure on GPU/TPU would be desirable.
- Experience with Agile Scrum methodology preferred.
- Demonstrated ability to manage projects independently and lead multifunctional teams and deliver end-to-end solutions
- Critical analytical thinking, problem-solving capabilities, and proven records of creative ideation and development of successful solutions
- Strong communication skills, both written and oral. Demonstrated ability to write comprehensive technical reports and deliver technical presentations
- Excellent planning and organizational skills
- Ability to interact constructively with colleagues from a wide variety of roles within the company
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Process Modeling Data Scientist - Bridgewater, United States - Ingredion
Description
Ingredion is hiring a Data Scientist who will be part of a multidisciplinary team focused on establishing In Silico experimentation capabilities and Artificial Intelligence technologies for product innovation. The Data Scientist will use expertise in statistics and programming to develop simulation models that will aid in faster process and product design.
This position requires some background of process development, modeling and process simulation in a manufacturing and/or R&D environment.
Core responsibilities:
#LI-JG1
We are an equal opportunity employer and value diversity at our company. Ingredion seeks to provide a work environment that is free from harassment and discrimination. We will not tolerate any form of discrimination based on race, color, religion, age, gender, gender identity, gender expression, national origin, ancestry, handicap or disability-mental or physical-marital status, sexual orientation, veteran status, disability resulting from military service, or any other classification protected by law ("protected classifications"). We are committed to establishing and maintaining a work environment where everyone is treated with dignity and respect.
Relocation Available:
No