Data Scientist

BASIC REQUIREMENTS

• A Bachelor's degree from an accredited university in an Engineering discipline, Data Science, Computer Science, Mathematics, Statistics, Analytics, or Information Systems.
• 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.
• This position is subject to the International Traffic in Arms Regulations (ITAR) which requires U.S. person status.
• This position entails access to export-controlled items and employment offers are conditioned upon an applicant's ability to lawfully obtain access to such items.

PREFERRED REQUIREMENTS

• 2+ years of industrial and/or analytics experience after graduation.
• In depth knowledge of statistical software packages and advanced analytics techniques.
• Proven success manipulating and applying advanced data and statistical analysis methods to manufacturing data.
• Knowledge and experience working in various coding languages, including Python, R, and SQL.
• Strong verbal and written communication skills. Excellent analytical skills.
• Ability to work in a self-directed team environment.
• Strong organizational skills.

Howmet is a world leader in the investment casting industry and is a leading supplier of superalloys, aluminum, and titanium components for aerospace, automotive, and commercial transportation applications. Our Wichita Falls location is on the front edge of the rapid growth in the aerospace and turbine industries. Nestled halfway between Dallas/Fort Worth, Texas and Oklahoma City, Oklahoma, our facility in Wichita Falls supplies jet engine components to some of the most trusted names in the Aerospace industry.

JOB SUMMARY

The Data Scientist positions will be located in the Howmet Wichita Falls facility and working in a close cross-functional team environment.

JOB RESPONSIBILITIES

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 operational, quality and engineering problems using big data. Identifying opportunities and deploying tools to drive continuous improvement through data analytics. Driving a data-driven culture across the organization through expanding applications and training. Interact with internal customers to drive validation trials, implement process improvements, and integrate predictive models using big data.