Data Scientist

The position of Data Scientist is an exciting opportunity to be a part of Corning’s Data Science & Intelligence team, which delivers analysis and insight to support high stakes strategic decisions and financial operations in a large and diverse Fortune 500 company. This role is part of the Finance Function and will be at the forefront of transforming decision science within corporate finance and across the company. The team leverages core competencies in: statistics, data science, and corporate finance. Projects will be approached as a team, with the Data Scientist expected to both complete independent analyses and engage collaboratively with the broader team.
Using advanced modeling techniques, the Data Scientists will provide objective and insightful analysis to all levels of the organization including Senior Leadership. The individual must possess competency in the application of data science methods to solve complex business problems. Commonly used methodologies include time series models, Bayesian modeling, tree-based methods, clustering, reinforcement learning, deep learning, and text-mining. The candidate should have interest in applying these methods to advance Corning’s decision-making capability within the Finance function.
Day to Day Responsibilities:
• Thinking creatively to frame business problem in terms of modeling analysis to support strategic decision making by using new and established methodologies in descriptive, predictive, perspective modeling
• Translating analysis results into business recommendations
• Supporting the Data Science Manager to identify and assess the right modeling methodologies to solve business problems
• Conducting research on state-of-the-art methodologies and experimenting with new machine learning methods to advance the group’s capabilities to deliver advance modeling solutions for high value business problems
• Sharing learnings and modeling results in presentations to different stakeholders
• Coaching junior Data Scientists
• Compiling and manipulating internal and external data sets for modeling
• Critically evaluating and recommending improvements to current approaches, models, metrics, and code to improve robustness and operational efficiency
• Contributing high quality code to project repositories
Required Education:
• MS or PhD in quantitative discipline (Mathematics, Statistics, Computer Science, Economics, Finance)
• Course work and/or experience in applied statistics, machine learning, or data science
• Course work and/or interest in Finance, Economics, or Operations Management is a plus
Required Qualifications:
• Ability to work both independently and as part of highly collaborative teams
• Able to convert research work into production to solve real problems
• Must be inquisitive and open to challenging traditional processes and thinking
• Self-driven for continual learning and ongoing training/development
• Able to present technical analysis to senior level stakeholders
• Track-record of publication in academic journals or conference is a plus
Technical Competencies:
• Strong competency with Python and the Python data science ecosystem
• Experience scripting with SQL
• Experience working in Linux/Unix environment
• Experience with git source control platforms like GitLab or GitHub
• Familiarity with development tools such as Docker is a plus
• Familiarity with Databricks, and AWS Machine Learning platforms is a plus
• Experience with distributed computational frameworks (Spark, Dask, etc) is a plus
This position does not support immigration sponsorship.

Keep in touch

Join our newsletter and stay up to date withe NABA Charlotte!