Data Scientist (Partial remote work available)

Join us as a Data Scientist at AIR. The role is partially remote and focuses on leveraging AI, machine learning, and advanced analytics to enhance institutional research and decision‑making.

Technical Competence in AI Tools & Frameworks:

• Deploy generative AI platforms (ChatGPT, Claude, MidJourney, Hugging Face) to enhance data analysis, reporting, and decision‑making.
• Use machine learning frameworks (TensorFlow, PyTorch, scikit‑learn) to support applied analytics projects.
• Integrate AI models via APIs and cloud platforms (AWS, Azure, GCP) to scale institutional solutions.
• Apply AI techniques such as NLP and generative modeling to analyze unstructured data (e.g., survey comments).
• Document assumptions, limitations, and risks to ensure responsible AI use and communicate results to non‑technical stakeholders.
• Lead or support workshops promoting best practices in AI and analytics.

Data Management:

• Use WhereScape and Microsoft SQL Server for data warehouse automation and efficient data management.
• Generate standardized reports with Cognos.
• Clean, preprocess, and organize datasets for reporting and modeling.
• Maintain data integrity through standards, validation, and documentation.
• Contribute to data initiatives involving metadata, data quality, model design, extraction, dashboard development, analytics tool evaluation, system configuration, and end‑user support.

Data Science & Advanced Analytics:

• Conduct advanced statistical, predictive, and prescriptive analysis using R, Python, and SQL.
• Develop and validate models (regression, random forests, neural networks) and scale prototypes into production.
• Apply forecasting and modeling to support academic and strategic planning.
• Write statistical designs, conduct analyses, and generate predictive insights.
• Analyze text data using NLP, topic modeling, and sentiment analysis.
• Run experiments (A/B testing) to evaluate and improve institutional initiatives.

Cross‑Functional Collaboration:

• Partner with offices such as the Registrar’s to promote data‑informed decision‑making.
• Collaborate with IT, architects, and analysts to design and manage analytics platforms aligned with strategic priorities.
• Serve as the data science expert on multi‑department projects, guiding end‑to‑end analytics processes.

Basic Analytics & Reporting:

• Support operational and strategic initiatives through data analysis projects.
• Apply statistical methods, querying, scripting, and data modeling to generate reports, dashboards, and visualizations.
• Conduct exploratory data analysis to identify trends and anomalies.
• Develop automated workflows to ensure consistent data delivery.
• Create engaging dashboards that communicate insights to diverse audiences, including campus leadership.

Strategy Development:

• Contribute to developing and executing data and analytics strategies with campus leadership.
• Support initiatives involving the enterprise data lake, data warehouse, BI tools, machine learning, and AI.
• Provide consulting and analytic guidance to align campus projects with institutional goals.

Non‑Essential Functions:

• Additional tasks may be assigned as needed.

• Bachelor’s degree and 4 years of professional experience in data science or a related field, OR Master’s degree and 2 years of professional experience in the same area.
• Experience designing, implementing, and administering data lakes, data warehouses, ETL or data warehouse automation solutions, and enterprise reporting platforms (Cognos, Business Objects, Microstrategy, or similar).
• Proficiency in SQL and strong programming skills in Python, R, or Java; experience with data wrangling, cleaning, and preprocessing.
• Expertise with data visualization tools (Tableau, Power BI, Qlik) and best practices.
• Knowledge of statistical models (GLMs, hierarchical models, non‑parametric models, regression trees, random forests) and solid understanding of descriptive and inferential statistics, probability, and experimental design.
• Ability to explain model assumptions, limitations, and results to non‑technical audiences.

• Familiarity with big data tools (Spark, Hadoop) and cloud environments (AWS, GCP, Azure).
• Experience with at least one version control tool such as Git, CVS, SVN, or similar.

• This role is based in a typical office setting without any unique physical or environmental requirements.

Bucknell University is a private, highly ranked, national liberal arts institution committed to academic excellence through diversity in its faculty, staff, and students. The university offers strong professional programs in engineering, business, education, and music, and is located in Central Pennsylvania.

• Flexible scheduling options determined by role.
• Medical, prescription drug, vision, dental, life, and long‑term disability insurance options.
• 10% employer contribution to retirement plan (no contribution requirement for non‑exempt positions).
• Generous paid time off, including vacation and sick time, a community service day, and 19 paid holidays.
• Tuition remission for eligible full‑time employees, and for their spouses/spousal equivalents and children where applicable.
• A comprehensive employee wellness program and other employee assistance benefits.
• Fitness center membership, parental leave, and other benefits.

Mid‑Senior level

Part‑time

Engineering and Information Technology

Non‑profit Organizations