This site uses cookies. To find out more, see our Cookies Policy

Data Science Associate - MFG in Cleveland, OH at Arconic

Date Posted: 12/3/2018

Job Snapshot

Job Description

Arconic Wheel and Transportation Products invented the first forged aluminum truck wheel in 1948—and by doing so, we created an entire industry. Seven decades later, we’re proud to be the global market leader in the forged, aluminum heavy-duty truck wheel market, holding the number one position. We’ve helped customers around the world to increase payload while saving fuel and reducing maintenance by switching out heavy steel wheels for lightweight aluminum.
 
The Data Science Associate - Manufacturing is responsible for analyzing AWTP data across processes and making recommendations. This position also investigates relationships among variables across a variety of functional disciplines but primarily manufacturing operations (e.g. performance metrics, cost components, quality data, design parameters, machine parameters, process characteristics, etc.).

Job Responsibilities and Duties:
  • Design and engineer data pipelines and analytics-ready datasets to which this role will be expected to apply a mix of operational and analytics expertise; 
  • Provide the opportunity to inject ideas and influence a growing data driven culture and gain operational experience with data science, analytics and engineering;
  • Perform “what if” analyses and question existing assumptions and processes;
  • Communicate insights and recommendations to both Operational and IT leaders;
  • Collaborate with Arconic Technical Center, Process Engineers and IT department to utilize hidden potential in the manufacturing systems;
  • Identify key data sources and develop scalable and repeatable methodologies and algorithms to capture and contextualize the data while correcting for limitations or errors (e.g. signal / noise ratio, sample size, inconsistencies, missing values, corruption, etc.);
  • Collaborate with experts and asks searching, probing questions to understand the business question(s), identify and contextualize data source(s), efficiently build analytics-ready datasets, and choose the appropriate analytics tools/techniques to develop insights and recommendations;
  • Convert existing Microsoft Excel data-based Continuous Improvement data sources and systems to web-enabled, SQL Server platform for global audience.
Major Activities and Key Challenges Include:
  • Key initiatives include the design and implementation of dashboards, development of key metrics, scorecards and the delivery of self-service analytics as well as streamlining and improve existing Continuous Improvement data sources, processes and systems;
  • Possess a hunger for data and a passion for researching tools and techniques for discovering new data sources as well as unlocking new uses for existing data sources;
  • Strong analytical and problem-solving skills needed to contextualize and transform data prior to analysis;
  • Solid understanding of statistical modeling tools and techniques;
  • Demonstrated problem-solving and pattern recognition skills (. e.g. algorithm development);
  • Desire to tell stories with data and help others to understand the value of our data assets.
#LI-GP1

Qualifications

Basic Qualifications:
  • Bachelor’s degree from an accredited institution;
  • Minimum of 3 years of experience in data analytics, statistics, data programming and / or computer science;
  • Experience working with one or more of the following languages: R/SQL/Python/C/C#;
  • Employees must be legally authorized to work in the United States.  Verification of employment eligibility will be required at the time of hire.  Visa sponsorship is not available for this position.
Preferred Qualifications:
  • Bachelor degree in Digital Science, Mathematics, Statistics, Computer Science, Information Science or Engineering from an accredited institution;
  • Minimum 5 years of experience in data analysis, statistics, data programming and / or computer science;
  • Experience or significant course work in statistical data analysis and related tools and techniques.