Scientist, Data Analytics

Corning•City of Corning, NY

1d•$71,337 - $98,089•Onsite

About The Position

This candidate will be responsible for using existing data and/or generating new data to solve technical, business, or project-related problems. The candidate should have experience with data capture using various software tools, managing and manipulating large datasets, and applying a wide variety of data analysis methods. The analytical work will support projects ranging from highly technical problems to business forecasting. This will also involve manufacturing, development, research, and commercial work. The incumbent will act as a subject matter expert within a team environment to provide data analytics; this may require the creation of novel computational methods and analytical models.

Requirements

M.S. or Ph.D. in engineering, computer science, mathematics, statistics, or a related discipline, with a specialization in data analytics
Capable of independently preparing data for machine learning purposes and performing exploratory data analysis.
Strong mathematical and programming skills.
Deep knowledge of state-of-the-art analytical methods and the software required to apply them.
Knowledge of machine learning techniques, including traditional machine learning and modern deep learning methods (e.g., convolutional neural networks, recurrent neural networks, transformers, and self-supervised learning).
Practical experience using machine learning and deep learning frameworks and libraries for large-scale data mining.
Must be collaborative and able to openly engage with colleagues to achieve project goals.
Self-motivated, with the ability to manage one’s own work independently.
Ability to communicate effectively by phone and video with team members at international locations.
Ability to take feedback constructively and use it for personal growth.

Nice To Haves

Knowledge of emerging technologies and algorithms in computer vision and/or machine learning in general.
Understanding of analytics platforms and the ability to build data analytics solutions that meet performance and scale requirements.
Familiarity with newer AI approaches such as foundation models and large language models (LLMs), generative AI, retrieval-augmented generation (RAG), and related tooling (e.g., prompt engineering, model evaluation, and/or MLOps practices for deployment and monitoring).

Responsibilities

Perform data analysis and interpret results in RD&E or business environments.
Work independently or as part of a team on data collection and preparation, followed by identification and application of appropriate analytical methods to solve problems or gain insight.
Participate on cross-functional teams to develop and test hypotheses to meet project objectives.
Develop new theories, or expand upon existing theories, as needed to solve complex problems.
Research external and internal information relevant to problems identified by the project team.
Collaborate with subject matter experts to solve challenging problems across a variety of (mostly technical) disciplines.