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Kaiser Aluminum · 18 hours ago

Data Scientist

Spokane, WA

Full-time

Onsite

Mid, Senior Level

$85K/yr - $150K/yr

Kaiser Aluminum is known around the world for its superior quality, and they are seeking a Data Scientist to join their onsite team in Spokane, Washington. The role involves analyzing, designing, testing, and implementing applications and integrations while focusing on product and process improvements through advanced data analytics.

AerospaceAutomotiveIndustrialManufacturing

No H1B

U.S. Citizen Only

Hiring Manager

Sean Hussey

Responsibilities

Conduct the low cost and high quality product and process improvement and optimization through the combination of advanced data analytics and ICME (Integrated Computational Material Science)

Monitor, evaluate, and apply the advanced computing technologies and algorithms for the most sophistic data analytics to uncover insights and hidden variables, identify root causes and patterns, forecast outcomes, and provide data-drive solutions

Production process data collection, high dimension large dataset multivariate analysis, classic and penalized regression predictive modelling, advanced neural-network and decision-tree based predictive modeling development and applications

Develop general and challenge specific predictive modeling capabilities by using commercially available software and/or internal computational codes

Design and development of alloys and processes for Aluminum products through advanced data analytics and ICME

Provide guidance and mentorship supports for different levels of data analytics including the principle and limits of different analytical algorithms

Provide support for Industry 4.0 initiatives

Develop, define, and complete on-time assigned research & development chartered projects

Support plant projects as directed

Write technical reports summarizing work as well as presentations to peers on progress at continuous improvement meetings

Perform metallurgical and structural analysis of aluminum products

Work in cross-functional teams to develop process and production improvements

5S of assigned areas

Qualification

Predictive modelingStatistical analysisData analyticsAluminum manufacturingMachine learningPythonSQLMaterial modelingContinuous improvementCommunication skillsTeamworkOrganizational skills

Required

MS degree in Data Science, or Computational Material Science, or Statistics, or Material Science or Mechanical Engineering is required

Excellent experience in statistical analysis and computing for data-driven problem solving in manufacturing environment

Strong skills and experience in predictive modeling development by using multivariate analysis, classic and penalized regression predictive modelling, advanced neural-network and decision-tree based predictive modeling technologies

Experience with the advanced computing technologies and algorithms, such as machine learning, to build high quality predictive modes, uncover insights and hidden variables, and provide solutions

Experience in large dataset collection, integration, and visualization by using Excel, SQL, Mintab, Python, etc

Background in aluminum manufacturing, physical, and mechanical metallurgy

Experience in thermodynamic and kinetic material modeling by using CALPHA principle, and process simulations by using FEA and CFD tools

An ability to apply continuous improvement tools and methodologies to processes and projects

Excellent communication skills (written and verbal) and organizational skills

Proven ability to work in teams

Ability to manage multiple tasks simultaneously