Career Opportunities: Engineering Data Scientist - Remote (126337)

Job Overview

BU Overview
Consumer, network, and data center applications change at an exponential pace and the Digital Data Networks (DDN) business unit at TE Connectivity is at the heart of a continuously expanding connected life. Accordingly, we provide responsive, iterative, and fundamentally agile capabilities and conceive, design, and manufacture to support today's demands. Our customers are building the devices and the infrastructure that is redefining what information technology means. Our products push markets and meet the ever-changing needs of the evolving, more connected, data-driven world. We are enhancing the way we do business, focusing on the most important things and staying agile and responsive to the needs of a faster, more connected world.

Job Overview
As a Staff Data Scientist in a Product Development team, you will focus on solving complex problems and helping stakeholders make data-driven decisions by leveraging quantitative methods. You will be expected to independently work on projects in the areas of synthesizing large volumes of information and extracting signals from data in an efficient, structured, methodical, and programmatic way.  You will work collaboratively within a broader cross-functional team of mechanical, manufacturing, signal integrity & operations to execute leading-edge product designs.  You will be the subject matter expert for the signal integrity performance of many products/platforms in all phases of the initial analysis through prototype fabrication & evaluation, and production verification testing.   You will drive front-end engineering value, enabling TE Connectivity's mission to address the world's most challenging high-speed problems. You will collaborate with a world-class multidisciplinary team to translate data into critical design decisions using data science to address a wide range of engineering challenges.  You will engage with internal customers across the enterprise to ensure analytic solutions meet their needs and drive results as well as external customers to communicate product performance through early engineering collaboration.
 

Short Description

Responsibilities:

• Analyze large amounts of information to discover trends and patterns.
• Interpreting data sets to drive product and process designs.
• Present information using data visualization techniques to all stakeholders including signal integrity, product development, and manufacturing engineers.
• Propose solutions and strategies to design challenges
• Collaborate with other engineering disciplines (PDE, SI/EE, and MPDE)
• Develop custom algorithms to apply to engineering data sets which includes mechanical and SI modeling as well as early product validation and process validation data sets
• Assess the effectiveness of modeled data to real-world data sets and propose solutions to correlation challenges.
• Develop processes and tools to more effectively/efficiently collect/store front-end data collection allowing for correlation and analysis of larger data sets as well as traceability.

What your background should look like:

• Bachelor’s degree in mechanical engineering, electrical engineering, or Data Science
• Minimum of 5 years of work experience in an engineering or quality role 
• Analyze large amounts of information to discover trends and patterns.
• Interpreting data sets to drive product and process designs.
• A solid understanding of electromagnetic theory and electrical circuit behavior 
• Present information using data visualization techniques to all stakeholders including signal integrity, product development, and manufacturing engineers.
• Propose solutions and strategies to design challenges
• Collaborate with other engineering disciplines (PDE, SI/EE, and MPDE)
• Develop custom algorithms to apply to engineering data sets which includes mechanical and SI modeling as well as early product validation and process validation data sets
• Assess the effectiveness of modeled data to real-world data sets and propose solutions to correlation challenges.
• Develop processes and tools to more effectively/efficiently collect/store front-end data collection allowing for correlation and analysis of larger data sets as well as traceability.
• Strong understanding of how mechanics and physics impact product electrical performance.
• Strong understanding of manufacturing capabilities and relative tolerances around SPAM (stamping, plating, assembly, molding)
• Be able to communicate directly with development engineering during the NPI phase regarding future potential product risks based on historical data analyses.
• Basic understanding of s-parameters and how to post-process data as well as manipulate data such that thorough analyses can be completed and correct correlations can be found.
• Have working-level knowledge of multiple data analysis tools such as R, Python, JMP, Minitab, SQL, AWS Services, Tableau, or equivalent. Ability to work in a global environment – able to accommodate varying time zones, fluent in English (verbal/written), able to collaborate with individuals across geographies
• The individual must be highly motivated, a quick learner, and able to work independently

Competencies