Rocco Panella, Ph.D.

610-703-6189 · panella.rocco@gmail.com · LinkedIn

Data Scientist with 10+ years building ML and data science solutions for large industrial organizations, specializing in chemical engineering and manufacturing applications.

Experience

Bridgestone — Akron, OH — Lead Data Tools Developer — Feb 2023 - Present

• Lead developer for ML digital twin for new tire tread material development.
  • Established CI/CD practices: version control (Git), automated testing, environment control, and monthly deployments.
  • Built physics-based multi-task learning in PyTorch predicting 50+ material properties from formulations. Reduced model training time from 20+ hours to 15 minutes.
  • Cut inference API costs 5× by designing an AWS Lambda-based architecture in collaboration with IT.
• Accelerated several products by 2–3 months via digital experimentation; ~$1MM/year in lab cost avoidance.
• Grew digital twin adoption 30× in 1.5 years; annual digital experiments scaled from hundreds to 10M+ through GUI improvements and expanded user workflows.
• Designed and launched reverse-problem flow enabling product recommendations from market targets.
• Managed 30+ users, addressing feedback on system accuracy and usability.

Columbia University, 2U — Instructor for Data Bootcamp — Feb 2023 - Aug 2023

• Taught Data Analytics and Visualization to 25 students; 9 hrs/week of instruction plus 3 office hours over 6 months.
• Live-coded across Python, SQL, and JavaScript; introduced AI coding assistants (Copilot, OpenAI).

Nestlé — Solon, OH — Senior Data Scientist — Mar 2021 - Feb 2023

• Built Nestlé NA manufacturing data mart (SSIS, SQL Server, Python); output fed VP of Manufacturing’s daily dashboard on factory downtime across North America.
• Deployed daily anomaly-detection pipeline on Databricks scanning point-of-sale data from every Walmart, Meijer, and Target in North America for product sales anomalies.

BGI — Akron, OH — Principal Engineer, Data Scientist — Sept 2017 - Mar 2021

• Principal investigator and developer for two US Navy SBIRs ($1MM and $3MM).
  • $1MM SBIR: NLP, unsupervised clustering, and CRISP-DM policy analysis on aircrew performance data. Findings presented as part of advising to Congress, informing aircrew training funding.
  • $3MM SBIR: Prototype system ingesting manuals and audio transcripts for aircrew training; resulted in 5-year contract renewal.
• Scrum master for team of 8 developers and data scientists.
• Employee of the Quarter, presented by CEO.

Intel Corporation — Chandler, AZ — Senior Development Engineer, Substrates and Packaging — Jul 2013 - Sept 2017

• Built and owned a computer vision system for automatic defect classification in a high-volume manufacturing factory (Python, C++, OpenCV, scikit-learn, SQL).
• Owned yield and quality reporting using Oracle, JMP, Python, and SQL; led 24/7 excursion response team and daily tactical response meetings.
• Developed interactive factory monitoring dashboards (SQL, Python, bokeh, matplotlib, pandas).

Education

Carnegie Mellon University, Pittsburgh PA — PhD Chemical Engineering — 2008–2013

• GPA 3.91/4.00 · National Science Foundation Graduate Fellow
• Teaching Excellence Award in 2 courses; taught 5 courses during studies.
• President, Chemical Engineering Graduate Student Association (ChEGSA)

Penn State University, State College PA — BS Chemical Engineering — 2004–2008

• GPA 3.94/4.00, Highest Distinction · President, Schreyer Honors College Student Council (2007)

Publications

• S. Ranjan, S. Balaji, R.A. Panella, B.E. Ydstie. “Silicon solar cell production.” Computers & Chemical Engineering, 2011. Best Paper Award.

Skills

Data Science and Development

• Advanced: Python (Pandas, PyTorch, scikit-learn, Streamlit), SQL, CI/CD platforms (GitHub, ADO, BitBucket)
• Basic: JavaScript, HTML, CSS
• Tools: VSCode, Databricks, AWS; proficient with AI coding assistants (Claude, Copilot)

Professional

• Requirements gathering and requirements-driven development.
• Team leadership using Agile and Scrum (Certified ScrumMaster).
• Experienced transforming data-immature organizations into cloud- and AI-enabled teams.