Data Scientist

Bucknell University

18h • Onsite

About The Position

Bucknell’s Office of Institutional Research and Analytics (OIRA) is a team of professionals who leverage data, analytics, and AI to deliver insights that support Bucknell in solving real-world challenges for students, faculty, and staff. The Data Scientist is principally responsible for collaborating with campus partners to execute Bucknell’s Data Analytics strategy, supporting tools and technologies, and supporting the strategic planning. Responsibilities span from understanding stakeholder needs to strategy development, promoting analytics adoption, executing daily operations, and planning for future capabilities. The role requires advanced problem-solving skills, adaptability, and the ability to manage complex projects with minimal supervision. Collaboration is essential, involving close work with OIRA colleagues, IT, University leadership, and external vendors to meet Bucknell’s evolving data and analytics needs.

Requirements

• Bachelor’s degree and four (4) years of professional experience in data science or a related data-focused field OR Master’s degree in Analytics, Data Science, Statistics, Computer Science, Information Systems, or a related field and two (2) years of professional experience in data science or a related data-focused field.
• The following knowledge areas and skills should be demonstrated in a professional setting, accompanied by two or more years of relevant experience:
• Build and maintain ETL processes and data pipelines supporting data lakes, data warehouses, and automated analytics workflows
• Work with relational and NoSQL databases to query, integrate, and manage data for enterprise reporting and analytics
• Develop analytics solutions using modern programming languages (e.g., Python, R, Java, or similar), with strong SQL skills and experience in data preparation and preprocessing
• Apply statistical and machine learning methods to analyze data, develop and tune predictive models, create effective visualizations, and clearly communicate insights to non-technical audiences
• Design and deploy generative AI and LLM-powered tools to automate insight generation and improve analytical workflows.

Nice To Haves

• Familiarity with big data tools (Spark, Hadoop) and cloud environments (AWS, GCP, Azure).
• Demonstrated experience with at least one version control tool such as Git, CVS, SVN, or similar.
• Prior experience in higher education setting.

Responsibilities

• Technical Competence in AI Tools & Frameworks: systems are responsibly implemented by documenting assumptions, limitations, and risks and communicating outcomes clearly to non-technical stakeholders. Lead or support workshops related to data science and AI, promoting best practices in analytics.
• Data Management: Use WhereScape and Microsoft SQL Server for data warehouse automation and efficient data management. Generate comprehensive and standardized reports using the Cognos reporting tool. Clean, preprocess, and organize datasets for reporting and modeling purposes. Establish standards, robust validation processes, and thorough documentation. Contribute technically to Data Analytics initiatives and systems as needed, including metadata and data definitions, data quality, model design, data migration and extraction, report/dashboard design and development, data analytics tool assessment, selection, and implementation, system configuration and maintenance, and end user support.
• Data Science & Advanced Analytics: Conduct advanced statistical analysis, machine learning, and predictive, prescriptive analysis using R, Python, and SQL. Develop and validate machine learning models (e.g., regression trees, random forests, neural networks) and scale prototypes into production. Apply forecasting techniques and advanced modeling to support academic and strategic planning. Assume primary responsibility for writing statistical designs, conducting analyses, and generating predictive insights. Analyze unstructured datasets (e.g., survey comments, text data) using natural language processing (NLP), topic modeling, and sentiment analysis. Run experiments (e.g., A/B testing) to evaluate and improve institutional initiatives.
• Cross-Functional Collaboration: Work closely with partners like the Registrar’s Office to foster a data-informed decision culture. Collaborate with IT, architects, engineers, analysts, and other colleagues to design, implement, and manage data analytics platforms that align with institutional strategic priorities. Serve as a data science expert on multi-department projects, guiding the full analytics process.
• Basic Analytics and Reporting: Support operational and strategic initiatives through data analysis projects. Apply statistical methods, querying, scripting, and data modeling to generate reports, dashboards, and interactive data products. Conduct exploratory data analysis (EDA) to identify patterns, anomalies, and correlations. Develop automated workflows to synthesize, validate, and consistently deliver data. Create engaging dashboards and visualizations that effectively communicate findings to diverse audiences, including campus leadership.
• Strategy Development: Participate in developing and executing information delivery and management strategies with campus leadership and stakeholders. Contribute to initiatives involving the enterprise data lake, data warehouse, BI & data analytics tools, ML/AI, and data management. Provide consulting support for campus stakeholders to align analytics work with strategic goals.
• The job description's listed responsibilities and tasks are not exhaustive, additional non-essential tasks and responsibilities may be assigned as needed.

Benefits

• Eligible full- and part-time employees are compensated beyond base salary through our total rewards package that includes (but is not limited to): Flexible scheduling options determined by role; Medical, prescription drug, vision, dental, life, and long-term disability insurance options An outstanding 10% employer contribution to your 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 (including two full weeks off for Winter Break!) Full-time and part-time members of the faculty and staff are eligible for tuition remission for themselves. Additionally, full-time members of the faculty and staff are eligible for tuition remission for their spouse/spousal equivalent and are eligible for various tuition programs for their children. Credit for full-time benefits eligible employment at other institutions of higher education will be applied to waiting periods. A comprehensive employee wellness program including program incentives A myriad of other benefits, including parental leave, an employee assistance program, fitness center membership, and the power of your Bucknell ID card

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 1,001-5,000 employees