CoE Data Systems Engineer in Springdale, AR at Arconic

Date Posted: 3/12/2018

Job Snapshot

Job Description

This opening is for our Center of Excellence (CoE) in Manufacturing group as a part of Arconic’s global Business and Construction Systems (BCS) business unit. We are the leading manufacturer of architectural aluminum products and systems for the commercial construction industry and our Kawneer brand manufactures and markets architectural systems and products in North America, Europe, Asia and the Middle East.

The CoE Data Systems Engineer is accountable for the development of data analytic strategies and systems capable of increasing the efficiency and problem-solving capabilities within BCS.

Please note this position requires the ability to work in Springdale, Arkansas Plant with the ability to relocate to Cranberry Twsp, PA within 15-18 months.

Job Responsibilities and Duties:

  • Organize, construct, and deploy systems capable of analyzing and displaying large amounts of data in formats that meet the organizational requirements;
  • Engage the organization deeper into problem solving efforts utilizing performance metrics, cost components, quality data, design parameters, machine parameters, process characteristics, etc., using various tools including but not limited to: Business Intelligence Suites, Databases (SQL and OSI PI), Reporting Tools, and Statistical Analytical Software;
  • Perform “what if” analysis and communicate recommendations to both operational and IT leaders. Collaborate with Arconic Technical Center, Process Engineers and IT resources to utilize hidden potential in the manufacturing systems;
  • Identify and correct data limitations (e.g. signal / noise ratio, sample size, inconsistencies, missing values, corruption, etc.);
  • Design and implement dashboards and key metric scorecards;
  • Determine potential causes of problems and devise testing methodologies for validation;
  • Explain the context of multiple inter-related situations developing multi-variate regression models;
  • Search and probe questions with peers and process experts that ultimately leads to action and recommendations;
  • Guide and direct small teams to achieve project objectives including the set up and execution of smart manufacturing deployment across BCS locations;
  • Streamline and improve existing data analytics tools within the continuous improvement processes and systems;
  • Use data, best practices and Kaizen methodologies to increase process efficiency and reduce operational cost.
Major Activities and Key Challenges Include:
  • Ability to enjoy data performing data analytics and discovering new data sources;
  • A deep understanding of SQL and employee interface tools to enhance data based problem solving;
  • A deep understanding of time series analysis and regression analysis;
  • Strong analytical and problem-solving skills with the ability to develop and use structured approaches to identify root causes and recommend solutions;
  • Ability to lead technical activities to meet timing and budgetary targets;
  • Good verbal and written communication skills;
  • A working knowledge of manufacturing processes and improvement strategies;
  • Ability to enjoy problem solving and relationship building across facilities;
  • Ability to tell stories with data, educate effectively, and instill confidence in recommendations;
  • Project Management skills to copy and paste existing best practices across the network;
  • Work with COE team members and automation engineers who will be responsible for Use Case execution and capex projects;
  • Work with location leaders and engineers on delivering cost savings through digitalization efforts.

    Basic Qualifications

    • Bachelor’s Degree in Computer Science, Data Sciences, Engineering or Engineering Technology from an accredited institution;
    • 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

    • Preferred experience in: Matlab, Statistics and Machine Learning, Neural Networks, R, Capstone DataPARC, modeFrontier, Azure, Power BI, Crystal Reports, SQL, SQL Report building Software and / or .Net;
    • Preferred experience in: various data systems and the ability to tailor and present data analytics methods and findings to leadership that drive effective decision making.