Data Scientist
- Bucknell University
- Lowry House
- 5mo ago
- Full-Time
- On-site
Position Title:
Data ScientistPosition Type:
Full timeScheduled Weekly Hours:
40Categories:
Staff ExemptJob Summary:
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’s solve 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.Job Duties:
To ensure a comprehensive review of your candidacy within the context of our unique academic mission, all applicants must submit a cover letter that directly addresses the following criteria: Your Compelling Reason & Alignment with Academic Success.
This is your opportunity to clearly articulate your genuine motivation for applying. Please provide a compelling reason why this specific Data Scientist role within our institution aligns with your professional aspirations and current skills. Your letter should not merely summarize your resume, but must demonstrate genuine intent by answering these two questions:
Why This Institution? What specifically about our academic mission, our commitment to student success, or the specific analytical challenges facing higher education excites you and motivates you to contribute?
Why You? Beyond the required technical skills listed, what unique perspective, passion, or non-obvious experience do you possess that makes you the ideal candidate to make a significant impact on institutional effectiveness and academic outcomes in this role?
The Data Scientist reports to the Chief Analytics Officer.
This is an in person role.
This is a full-time, exempt, 40 hour per week role.
Technical Competence in AI Tools & Frameworks: Deploy generative AI platforms (e.g., ChatGPT, Claude, MidJourney, Hugging Face) to enhance data analysis, reporting, and decision-making. Use machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) to support applied analytics projects. Integrate AI models via APIs and cloud platforms (AWS, Azure, GCP) to scale solutions for institutional use. Apply AI techniques such as natural language processing and generative modeling to analyze unstructured data (e.g., survey comments, text datasets). Ensure AI 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: Utilize 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. Ensure data integrity by implementing standards, validation processes, and 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 deliver data consistently. 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.
Non-Essential Functions: The job description's listed responsibilities and tasks are not exhaustive, additional non-essential tasks and responsibilities may be assigned as needed.
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.
Two (2) or more years experience with designing, implementing, and administering: Data Lakes and Data Warehouses; ETL or data warehouse automation solutions; Enterprise reporting platforms (Cognos, Business Objects, Microstrategy, or similar); Data visualization platforms (Tableau Server/Cloud, Power BI, Qlik, or similar); Relational and NoSQL database platforms like Microsoft SQL Server, MySQL, Oracle, MongoDB, and DocumentDB.
Knowledge Areas and Skills: Proficiency in SQL and strong programming skills with experience in one or more modern programming languages (e.g., Python, R, Java or similar); Experience with data wrangling, cleaning, and preprocessing; Expertise with data visualization tools and best practices; Knowledge of various statistical models (e.g., generalized linear models, hierarchical models, nonparametric models, regression trees, random forests) and a solid understanding of descriptive and inferential statistics, probability, and experimental design; Ability to explain model assumptions, limitations, and results to non-technical audiences.
Preferred, but Not Required:
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.
This role is based in a typical office setting without any unique physical or environmental requirements.
Job Exempt:
YesSalary Range:
72,640.00-90,800.00The offer rate will be based on a review of the candidate's credentials compared to the qualifications of the position, internal equity, and our overall compensation philosophy.
This role is not budgeted for visa sponsorship at this time, all candidates must be authorized to work in the US at the time of submission of the application.
Benefits:
Eligible full- and part-time employees are compensated beyond base salary through our total rewards package that includes (but is not limited to):
To learn more about Bucknell's benefits, click here! (*Eligibility criteria and waiting periods may apply.)
Inclusive Excellence:
Bucknell is committed to fostering an environment that embraces diversity, equity and inclusion, and seeks candidates who will contribute to a climate that supports the growth and development of a diverse campus community. We endeavor to enhance our capacity to value and capitalize on the cultural richness that diversity brings. We encourage all individuals to apply and do not discriminate in admissions, employment, educational programs and/or activities on the basis of race, color, national or ethnic origin, age, religion, disability, pregnancy, sex/gender, gender identity and/or expression, sexual orientation, marital or family status, military or veteran status, or genetic information.
E-Verify
Bucknell University participates with the United States Customs and Immigration Services (USCIS) E-Verify program. We will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.
For additional information regarding Bucknell's E-Verify requirements, please contact the office of Talent, Culture & Human Resources (570) 577-1631 or email hr@bucknell.edu.