Analyst Engineer (Finance)

Howmet Aerospace Inc. (NYSE: HWM), headquartered in Pittsburgh, Pennsylvania, is a leading global provider of advanced engineered solutions for the aerospace and transportation industries. Our primary businesses focus on jet engine components, aerospace fastening systems, titanium structural parts and forged wheels. With $7.4 Billion in revenue in 2024, our products play a crucial role in enabling fuel efficiency and lightweighting, contributing to our customers' success and making a positive impact on the world. To learn more about the way Howmet Aerospace Inc. is advancing the sustainability of our customers, markets, and communities where we operate, review the 2024 Environmental Social and Governance report at www.howmet.com/esg-report . Follow: LinkedIn , Twitter , Instagram , Facebook , and YouTube .

Equal Opportunity Employer:

Howmet is proud to be an Equal Employment Opportunity and Affirmative Action employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or other applicable legally protected characteristics.

If you need assistance to complete your application due to a disability, please email TalentAcquisitionCoE_Howmet@howmet.comBasic Qualifications:

• Bachelor's Degree in STEM from an accredited institution is required
• Must have experience in basic SQL querying skills
• Demonstrated ability to transform data with a programming language
• Strong working knowledge of Microsoft Office skills (Word, Excel, Powerpoint, Visio)
• 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. ITAR defines U.S. person as an U.S. Citizen, U.S. Permanent Resident (i.e. 'Green Card Holder'), Political Asylee, or Refugee.

Preferred Qualifications:

• 2 or more years of professional data science experience is preferred
• Previous manufacturing / industrial plant experience is highly desired
• A strong interest in working in a manufacturing environment
• Ability to work in a self-directed and cross-functional team environment
• An unquenchable desire to continuously learn
• Experience in applying advanced data and statistical analysis methods to industrial manufacturing data
• Visualization tools: Power BI, Tableau
• Experience with engineering data tools such as: SQL, SAS, Minitab, JMP, MS Excel, Six Sigma
• In depth knowledge of advanced analytics techniques.
• Strong verbal and written communication skills.
• Ability to work in a self-directed AND cross-functional team environment.
• Strong organizational and analytical skills

As an Analyst Engineer at the Howmet Research Center, you will join a team of Data Scientists and Machine Learning Engineers. This team is part of a multidisciplinary R&D group responsible for advancing the state-of-the-art in aerospace manufacturing at our casting, alloy, core and rings manufacturing facilities. You are a great fit for this team if you have the innate curiosity necessary to learn new processes, meet new people, and are persistently detail-oriented with a quality mindset. If you enjoy matching complex physical processes to corresponding data across multiple data sources, and transforming data into reliable, documented datasets for use in machine learning, reporting, and visualization tools, we would love to talk with you!

Primary Responsibilities

• Initiate working with manufacturing plant personnel to understand the detailed manufacturing process and data collection user interfaces
• Initiate working with corporate and local IT to understand the data storage and sources that correlate to the plant process, and the most efficient way to query them
• Query multiple data sources and join the data together to accurately represent the process
• Explore the data to identify edge cases, data cleaning requirements, and bias - using statistics as necessary
• Down-select, augment, and clean the dataset
• Iterate the above steps to generate a representative and reliable dataset, checking your own work and being able to explain it to others at multiple levels of the organization
• Collaborate with Data Scientists and Machine Learning Engineers to understand model input requirements
• Transform the data to meet machine learning model input requirements
• Provide post-modeling functions to translate model results to process-relatable values
• Actively participate in leveling up proof-of-concept code to productionized scripts
• Document projects in Power Point and reusable code, storing work in a revision-controlled system