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Advanced Analytics Intern

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Date: Jan 5, 2023

Location: Charlotte, NC, US, 28216

Company: Corning

Requisition Number: 59097

 

Corning is vital to progress – in the industries we help shape and in the world we share.

We invent life-changing technologies using materials science. Our scientific and manufacturing expertise, boundless curiosity, and commitment to purposeful invention place us at the center of the way the world interacts, works, learns, and lives.

Our sustained investment in research, development, and invention means we’re always ready to solve the toughest challenges alongside our customers. 



Our Optical Communications segment has recently evolved from being a manufacturer of optical fiber and cable, hardware and equipment to being a comprehensive provider of industry-leading optical solutions across the broader communications industry.This segment is classified into two main product groupings – carrier network and enterprise network. The carrier network product group consists primarily of products and solutions for optical-based communications infrastructure for services such as video, data and voice communications. The enterprise network product group consists primarily of optical-based communication networks sold to businesses, governments and individuals for their own use.

 

Purpose of the Position:

  • Develop technical solutions to complex commercial, financial and business problems, which require the regular use of sophisticated analytic and data science techniques.
  • Leverage data mining to discover trends and patterns from disparate datasets
  • Prepare data visualization in order to effectively communicate findings and insights with cross functional teams
  • Perform business problem modeling and quantitative analytics support activities for group using established tools and practices, including stochastic modeling, regression analysis, time-series analysis and data mining.

 

Day to Day Responsibilities:

  • Explore new analytic techniques, including time series modeling algorithms and optimization, and evaluate for current and future problems
  • Develop and evaluate performance of regression models with the goal of finding meaningful indicators and relationships between variables
  • Explore ensemble algorithms for improving forecasting accuracy of internal and external forecasts

 

Education & Experience:

  • Enrolled in quantitative (Mathematics, Statistics, Computer Science, Economics, Finance, Physics, Engineering) B.A. or B.S. or Advanced degree program
  • Required course work completed to include: Statistics / Probability
  • Recommended course work completed to include: Modeling/Data Visualization, Machine Learning, Financial Analytics, Marketing Analytics
  • GPA of 3.25 or above
  • Relevant experience a plus

 

Required Skills:

  • Fluency in Python or R
  • Computer literate in MS Office programs (Word, Excel, PowerPoint)
  • Problem-solving skills
  • Organizational skills
  • Demonstrated ability to manage multiple tasks
  • Ability to build relationships and interact with all levels of the organization
  • Excellent verbal and written communication skills; ability to effectively present technical information
  • Results-oriented
  • Flexibility - Able to change and adjust smoothly as the situation demands

 

Desired Skills:

  • Experience with data visualization tools (Tableau, PowerBI)
  • SQL

 

Hours of work / work schedule / flex-time  Basic work hours are 40hrs/week; 8am-5pm

 

This position does not support immigration sponsorship.

 

We prohibit discrimination on the basis of race, color, gender, age, religion, national origin, sexual orientation, gender identity or expression, disability, veteran status or any other legally protected status.

 

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.


Nearest Major Market: Charlotte