Analyst Engineer

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    "CorporateDescriptionStr": "<p>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 $8.3 Billion in revenue in 2025, 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 2025 Environmental Social and Governance report at <a href=\"https://www.howmet.com/esg-report/\" target=\"_blank\" rel=\"nofollow\">www.howmet.com/esg-report</a>. Follow: <a href=\"https://www.linkedin.com/company/howmet-aerospace\" target=\"_blank\" rel=\"nofollow\">LinkedIn</a>, <a href=\"https://twitter.com/howmetaerospace\" target=\"_blank\" rel=\"nofollow\">Twitter</a>, <a href=\"https://www.instagram.com/howmetaerospace/\" target=\"_blank\" rel=\"nofollow\">Instagram</a>, <a href=\"https://www.facebook.com/Howmetaerospace/\" target=\"_blank\" rel=\"nofollow\">Facebook</a>, and <a href=\"https://www.youtube.com/howmetaerospace\" target=\"_blank\" rel=\"nofollow\">YouTube</a>.</p>\n<p>Equal Opportunity Employer:</p>\n<p>Howmet is proud to be an Equal Employment Opportunity employer. We 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.</p>\n<p>If you need assistance to complete your application due to a disability, please email <a href=\"mailto:[email protected]\" target=\"_blank\" rel=\"nofollow\">[email protected]</a></p>",
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    "ExternalQualificationsStr": "<p>Basic Qualifications</p><ul><li>&nbsp;Bachelor’s degree in Engineering, Data Analysis, Data Science,&nbsp;Computer&nbsp;Science,&nbsp;or Information&nbsp;Systems</li><li>Must have experience in basic SQL querying skills</li><li>Demonstrated ability to transform data with a programming language</li><li>Strong working knowledge of Microsoft Office skills (Word, Excel, Powerpoint, Visio)</li><li>​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.</li><li>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.</li></ul><p>Preferred Qualifications</p><ul style=\"list-style-type:disc;\"><li style=\"tab-stops:list .5in;\"><span>Prior experience in a manufacturing environment&nbsp;</span></li><li style=\"tab-stops:list .5in;\"><span>On-the-job experience using python for data transformation, analysis, and visualization&nbsp;&nbsp;</span></li><li style=\"tab-stops:list .5in;\"><span>Intermediate-to-Advanced SQL querying knowledge (window functions, pivots, etc.)&nbsp;</span></li><li style=\"tab-stops:list .5in;\"><span>On-the-job experience with visualization tools such as Power BI or Tableau</span></li><li style=\"tab-stops:list .5in;\"><span>Experience with other engineering data tools: SAS, Minitab, JMP, Advanced MS Excel</span></li><li style=\"tab-stops:list .5in;\"><span>Familiarity with Six Sigma methodology or intermediate statistics&nbsp;</span></li><li style=\"tab-stops:list .5in;\"><span>Azure Data Lake and Databricks experience&nbsp;</span></li><li style=\"tab-stops:list .5in;\"><span>Familiarity with Git revision control&nbsp;</span></li><li style=\"tab-stops:list .5in;\"><span>Strong written and verbal communication skills&nbsp;&nbsp;</span></li><li style=\"tab-stops:list .5in;\"><span>Demonstrated ability to work effectively in a collaborative and matrixed team environment</span></li></ul><p>&nbsp;</p>",
    "InternalQualificationsStr": "<p>Basic Qualifications</p><ul><li>&nbsp;Bachelor’s degree in Engineering, Data Analysis, Data Science,&nbsp;Computer&nbsp;Science,&nbsp;or Information&nbsp;Systems</li><li>Must have experience in basic SQL querying skills</li><li>Demonstrated ability to transform data with a programming language</li><li>Strong working knowledge of Microsoft Office skills (Word, Excel, Powerpoint, Visio)</li><li>​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.</li><li>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.</li></ul><p>Preferred Qualifications</p><ul style=\"list-style-type:disc;\"><li style=\"tab-stops:list .5in;\"><span>Prior experience in a manufacturing environment&nbsp;</span></li><li style=\"tab-stops:list .5in;\"><span>On-the-job experience using python for data transformation, analysis, and visualization&nbsp;&nbsp;</span></li><li style=\"tab-stops:list .5in;\"><span>Intermediate-to-Advanced SQL querying knowledge (window functions, pivots, etc.)&nbsp;</span></li><li style=\"tab-stops:list .5in;\"><span>On-the-job experience with visualization tools such as Power BI or Tableau</span></li><li style=\"tab-stops:list .5in;\"><span>Experience with other engineering data tools: SAS, Minitab, JMP, Advanced MS Excel</span></li><li style=\"tab-stops:list .5in;\"><span>Familiarity with Six Sigma methodology or intermediate statistics&nbsp;</span></li><li style=\"tab-stops:list .5in;\"><span>Azure Data Lake and Databricks experience&nbsp;</span></li><li style=\"tab-stops:list .5in;\"><span>Familiarity with Git revision control&nbsp;</span></li><li style=\"tab-stops:list .5in;\"><span>Strong written and verbal communication skills&nbsp;&nbsp;</span></li><li style=\"tab-stops:list .5in;\"><span>Demonstrated ability to work effectively in a collaborative and matrixed team environment</span></li></ul><p>&nbsp;</p>",
    "OrganizationDescriptionStr": "<span>The Howmet engines business produces world-class aerospace engine</span> <b> </b> <span>components, including investment castings, fasteners, rings and forgings. Our vacuum melted superalloys, machining, performance coatings and hot isostatic pressing for high performance parts enable the next generation of quieter, cleaner and more fuel-efficient aerospace engines. Able to supply more than 90% of structural and rotating aerospace engine components.</span> <br/> \n<ul style=\"margin-top:0in;\">\n</ul>",
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    "ExternalResponsibilitiesStr": "<p>As an Analyst Engineer at the Howmet Research Center, you will join a team of Data Scientists and Machine Learning Engineers.&nbsp;This team is part of a multidisciplinary R&amp;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!</p><p><strong>Primary Responsibilities</strong></p><ul><li>Initiate working with manufacturing plant personnel to understand the detailed manufacturing process and data collection user interfaces</li><li>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</li><li>Query multiple data sources and join the data together to accurately represent the process</li><li>Explore the data to identify edge cases, data cleaning requirements, and bias – using statistics as necessary</li><li>Down-select, augment, and clean the dataset</li><li>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</li><li>Collaborate with Data Scientists and Machine Learning Engineers to understand model input requirements</li><li>Transform the data to meet machine learning model input requirements</li><li>Provide post-modeling functions to translate model results to process-relatable values</li><li>Actively participate in leveling up proof-of-concept code to productionized scripts</li><li>Document projects in Power Point and reusable code, storing work in a revision-controlled system</li></ul>",
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