Internship Meta Data Science Jobs in Pennsylvania

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 www.howmet.com/esg-report. Follow: LinkedIn, Twitter, Instagram, Facebook, and YouTube.

Equal Opportunity Employer:

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.

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

Essential knowledge, skills and abilities:

• Strong analytical and problem-solving skills with attention to detail.
• Excellent verbal and written communication skills with the ability to explain technical concepts to a variety of audiences.
• Demonstrates curiosity, initiative, and a willingness to continuously learn new technologies and analytical techniques.
• Ability to manage multiple assignments while meeting deadlines.
• Strong organizational skills and ability to document work effectively.
• Ability to work collaboratively in a team-oriented environment.
• Basic understanding of statistical analysis and machine learning concepts.

Basic Qualifications:

• Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Information Systems, or a related quantitative discipline.
• 0-2 years of experience in data science, analytics, software development, or a related field, including internships, co-op programs, undergraduate research, or equivalent project experience.
• Working knowledge of Python and SQL.
• Basic understanding of statistics, probability, machine learning concepts, and data visualization.
• 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:

• Internship, co-op, academic research, or personal project experience involving analytics, machine learning, or artificial intelligence.
• Experience with Python libraries such as:
• Machine Learning: Scikit-learn, TensorFlow, PyTorch, or similar frameworks.
• Data Analysis: Pandas, NumPy.
• Visualization: Matplotlib, Seaborn, or Plotly.
• Basic familiarity with cloud platforms such as Oracle Cloud Infrastructure (preferred), AWS, Azure, or Google Cloud.
• Exposure to Jupyter Notebooks, Git, Docker, or basic MLOps concepts.
• Exposure to Large Language Models (LLMs) and Generative AI concepts through coursework, internships, research, or personal projects.
• Familiarity with AI frameworks and libraries such as LangChain, LlamaIndex, Hugging Face Transformers, or similar tools.
• Experience using commercial or open-source LLMs (e.g., OpenAI, Anthropic, Meta Llama, Mistral) through APIs or local deployments.
• Basic understanding of Retrieval-Augmented Generation (RAG), prompt engineering, vector databases, embeddings, and semantic search concepts.
• Experience with Power BI  or similar visualization tools is beneficial.

This position is an opportunity to convert a current temp-to-hire role into a permanent position.

Salary Range: $38k - $43k/year approximation (actual compensation is subject to variation due to factors such as education, experience, skillset, and/org location).

Howmet Aerospace Inc. ("Howmet") is currently in search of a Data Scientist join the Global Information Systems (GIS) organization at the Howmet Corporate Center in Pittsburgh, PA. 

In this role you will be responsible for developing and deploying artificial intelligence models and applications. 

Major activities/Key challenges:

• Data Analysis and Model Development
  • Assist in developing, training, and evaluating machine learning models to solve business problems under the guidance of senior team members.
  • Perform exploratory data analysis to identify trends, patterns, and opportunities within business data.
  • Support feature engineering, model validation, and performance evaluation.
• Data Preparation and Management
  • Collect, clean, transform, and validate data from multiple sources to ensure quality and usability. 
  • Develop and maintain datasets for analytics and machine learning projects. 
  • Collaborate with data engineers and business teams to understand data requirements and improve data quality.
• Analytics and Reporting
  • Develop dashboards, reports, and visualizations that communicate insights to business stakeholders. 
  • Present findings and recommendations using clear data storytelling techniques. 
  • Assist with ad hoc analyses to support operational and strategic initiatives.
• Model Deployment and Support
  • Support the deployment, testing, and monitoring of machine learning models in production environments.
  • Assist in documenting models, code, and analytical processes.
  • Help troubleshoot data and model performance issues.
• Research and Innovation
  • Stay current with emerging trends in data science, machine learning, analytics, and artificial intelligence.
  • Learn and apply new analytical techniques, tools, and best practices.
  • Participate in knowledge sharing and team learning activities.
• Collaboration and Communication
  • Work closely with data scientists/AIML Engineers, data engineers, software developers, and business stakeholders on cross-functional projects.
  • Communicate technical findings in a clear and concise manner appropriate for both technical and non-technical audiences.