Manufacturing - Post-Doctoral Research Scientist

Postdoctoral Fellow - Natural Language Processing (NLP) and Artificial Intelligence (AI) Responsibilities: Utilizes supervised or unsupervised methods, learning from vast amounts of unlabeled data to drive insight from unstructured text Ensures life cycle managementof code is maintained through version control and associated repositories. Develops high quality analytical and statistical models, insights, patterns, visualizations, that can be used to improve decision making in manufacturing operations. Responsible for documentation of all technical work both within and outside of formal document management systems Independently develops code and analytical models to automate data transformation and analysis Performs data engineering, preprocessing, exploratory data analysis, and model development by interacting with a variety of databases Responsible for ingestion, integration and delivery of data across multiple platforms Works to maintain and uphold data integrity and clean data principles Communicates with team members regularly to provide updates and collaborate on deliverables. Displays a high level of teamwork and collaboration both within and across functions Requirements: PhD with knowledge of deep learning methods for NLP (quantitative area of study, Computer Science, preferred) Strong background and demonstrable experience in Natural Language Processing and Computational Linguistics is required Proficient in writing and developing analytical and machine learning models using python modules including pandas, numpy, scikitlearn, and tensorflow. Experiencing developing and implementing MLOps pipelines. Experience building analytical and statistical models to answer key business questions Experience using git via the command line Strong understanding of core statistical concepts to solve real world problems Intermediate to advanced proficiency (3+ years post academia experience as an independent contributor designing and delivering data solutions) in SQL. Experience interacting with various data warehouses and large-scale, complex datasets using ETL and BI tools and platforms. Self-motivated to identify and propose Client methodologies that will drive increased efficiency Demonstrate expert knowledge in machine learning and rule-based systems as applied to computational linguistics and natural language processing, as well as development and execution of annotation tasks with teams of experts Proficiency in mathematics with the skill to translate complex mathematical algorithms into usable computational methods Experience with data mining and analysis techniques across disparate data sources Experience working in LINUX/UNIX environments Experience interacting with PostgresSQL, Oracle, Impala Cloudera, Okera or similar databases Experience with JupyterLabs, Anaconda, and RStudio Intermediate proficiency with python Experience developing visualizations using a variety of methods (plotly, matplotlib, seaborn) Experience working within Domino Data Lab projects Technical knowledge of performance tuning and query optimization across large data sets. Experience with data cataloguing and enablement through APIs Experience with a variety of computer science languages (C++, Java, html/css) Exposure to bioprocess engineering/cell therapy data Knowledge of GxP requirements (preferably related to data and code management) Preferred: Dashboard development experience (Tableau, Spotfire, DASH) Experience working with the pharmaceutical industry