Support R&D project planning activities by estimating costs and durations of optimization related activities.
Collaborate with IT and subject matter experts (SMEs) to provide wholistic solutions that solve manufacturing and/or business-oriented optimization and analytics challenges.
Collaborate with Data Engineering resources to define appropriate data preprocessing, management, and storage needs supporting the optimization algorithms.
Identify and translate industrial use cases into formal optimization problem statements with constraints and objectives.
Provide leadership and expertise in the application and utilization of advanced optimization and statistical tools and methods.
Regularly communicate details, benefits, and challenges of implementing optimization algorithms to stakeholders with varied backgrounds.
Drive projects to completion and effectively communicate results through reports, patents, and/or presentations.
Program the mathematical models within algorithms using commercial and/or open-source computational tools and frameworks.
Convert optimization problem statements into detailed mathematical formulations and models.
Requirements
opl
cplex
gurobi
python
machine learning
ph.d.
Demonstrated experience in creating mathematical models in optimization programming language (OPL) using solvers such as GLPK and/or CPLEX.
Intermediate programming skills with computational optimization environments such as (but not limited to) CPLEX, Gurobi, and/or GLPK.
Competency in classical statistical methods including hypothesis testing, generalized linear models, multivariate methods, and/or time series analysis.
3 or more years of experience in developing and applying optimization and/or scheduling solutions.
Proficiency in using machine learning techniques to model complex systems.
Competency in Reliability methods including parametric modeling, survival analysis, tolerance intervals, and event driven analytics.
Master of Science (M.S.) Degree in Industrial Engineering, Mechanical Engineering, Electrical Engineering, Chemical Engineering, Operations Research, Computer Science, Statistics, Data Analytics, Data Science, or a related quantitative field with a focus in Optimization.
Intermediate programming skills with scripted programming languages such as (but not limited to) R, Python, and/or Matlab.
730, et seq.) and/or the International Traffic in Arms Regulations (ITAR). Authorizations from the relevant government agency may be required to meet export control compliance requirements.
Proficiency in Quality methods including Statistical Quality (Process) Control and measurement capability and analysis.
This position requires access to controlled technology, as defined in the Export Administration Regulations (15 C.F.R.
Proficiency in Heuristic Optimization methods such as (but not limited to) Genetic Algorithms, Simulated Annealing, Particle Swarm, and Ensemble Methods.
Ph.D. Degree in Industrial Engineering, Mechanical Engineering, Electrical Engineering, Chemical Engineering, Operations Research, Computer Science, Statistics, Data Analytics, Data Science, or a related quantitative field with a focus in Optimization.
Attention to detail within daily working habits.
Proficiency in general optimization with focus on Operations Research (Linear Programming, Combinatorial Optimization, Mixed-Integer Programming, Dynamic Programming).
Ability to develop innovative and practical solutions to complex problems without direct technical supervision.
Competency in relational databases such as (but not limited to) MS-SQL, PostgreSQL, MySQL, and/or SQLite.
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.
Strong written and verbal communication skills (technical writing and presentation).
3 or more years of experience in industrial operations, logistics and supply chain, and/or manufacturing environments.
Experience performing Exploratory Data Analysis (EDA), data manipulation/transformation, and applying data preprocessing techniques.
Benefits
Information not given or found
Training + Development
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Interview process
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Visa Sponsorship
visa sponsorship is not available for this position.
Security clearance
Information not given or found
Company
Overview
Designs and manufactures innovative engineered products for industries like aerospace, automotive, and industrial sectors.
Formed from the spin-off of Alcoa's engineered products division, emphasizing precision and advanced technologies.
Delivers solutions integral to some of the world's most demanding industries, improving performance, efficiency, and sustainability.
Proud legacy of innovation, with decades of experience in materials science and engineering.
Notable projects include aerospace components, automotive lightweighting solutions, and advanced industrial materials.
Products are used in everyday applications, from aircraft engines to consumer electronics, making a significant impact on global infrastructure.
Culture + Values
We are committed to safety in everything we do.
We act with integrity, fairness, and transparency.
We hold ourselves and each other accountable for delivering results.
We build lasting relationships with customers and create value by meeting their needs.
We drive innovation by fostering a culture of continuous improvement.
We are committed to responsible environmental practices that benefit people and the planet.
Environment + Sustainability
20% Improvement
Energy Efficiency
Achieved a 20% improvement in energy efficiency over the past five years through innovative production methods and process optimizations.
Net-Zero by 2050
Greenhouse Gas Emissions Goal
Committed to achieving net-zero greenhouse gas emissions by 2050, aligning with global sustainability targets.
Focus on reducing the carbon intensity of production processes.
Offering sustainable products such as aluminum for lightweighting and energy-efficient solutions.
Active engagement in circular economy practices, including aluminum recycling.
Inclusion & Diversity
30% Women Leadership Goal
Women in Leadership
Aim to achieve 30% representation of women in leadership positions by 2025.
Tracks and reports on gender diversity and inclusion efforts annually.
Promotes a culture of respect and inclusion through leadership development and training programs.