Data Scientist

Responsibilities

As a

data scientist

you will be working on a cross-functional team environment supporting Howmet’s casting, core, and rings facilities. This position involves:

• Up to 50% travel to support plants in France, UK and Germany
• Constructing and manipulating large datasets using tools like SAS, SQL, Python, R, MiniTab, PowerBI, and more to extract multi-factor interactions and drive change
• Solving manufacturing, quality, and engineering problems using data analytics and science tools.
• Identifying opportunities and deploying tools to drive continuous improvement through data analytics and science
• Driving a data-driven culture across the organization through expanding applications and training.
• Interacting with internal customers to drive validation trials, implement process improvements, and integrate predictive models using big data

Qualifications

Basic Qualifications:

• A bachelor’s degree from an accredited university in Materials Science and Engineering, Data Science, Computer Science, Mathematics, Statistics, Analytics, or related
• 2\+ years of professional data experience or a graduate data science degree
• Demonstrated success applying advanced statistical methods and/or machine learning algorithms to production/field data using Python or R
• 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:

• 2\+ years of professional data science experience
• Manufacturing/industrial plant experience
• Experience in applying advanced data and statistical analysis methods to industrial manufacturing data
• Visualization tools: Power BI, Tableau
• Engineering data tools: SQL, SAS, Minitab, JMP, MS Excel, Six Sigma
• In depth knowledge of advanced analytics techniques.
• Strong verbal and written communication skills. Excellent analytical skills.
• Ability to work in a self-directed AND cross-functional team environment.
• Strong organizational skills.