Situated in a historic neighborhood in the nation’s capital, Georgetown University offers rigorous academic programs, a global perspective, and exciting opportunities to engage with Washington, D.C., all while maintaining a strong commitment to social justice. Our community consists of a tight-knit group of remarkable individuals passionate about intellectual inquiry and making a meaningful difference in the world.

Requirements

The Georgetown University Graduate Data Science and Analytics Program invites applicants for a full-time, non-tenure line position as an Assistant Teaching Professor.

The successful candidate will teach three graduate-level courses per semester (Fall and Spring) and will participate in administrative tasks, such as admissions and advising.

This is a non-tenured teaching position, where the core focus will be on course development (traditional and online), teaching, student support, and administrative tasks such as student support, admissions, and committee participation. The teaching component (85-90%) includes 6 class sections (30 – 40 students each) per year with summers as a potential option. The administrative component varies with need and ranges from 10 – 15%.

Please note, this is not a research position. While research is highly regarded and encouraged, it is completed on the faculty member’s own time and is not contained within the requirements of this position. This position is also not connected to the option of transitioning into a tenure-line or research position. There is no avenue to translate from a non-tenure teaching position into a tenured position. If you are interested in a tenure-line and research-focused position, please do not apply to this advertisement. 

All new hires will be signed for a one-year initial contract to assure a good match. The renewal will be for a three-year term pending a committee review.  This academic appointment is August 1, 2025 to May 31, 2026 and the renewal will be from June 1, 2026 to May 31, 2029. Contracts are renewable after each contract term and depend on yearly reviews, performance, and committee review and approval.

The Data Science and Analytics Program offers a Master of Science degree in Data Science and Analytics and a BS(BA) – MS 5-year accelerated program in Data Science and Analytics. Ideal candidates will possess excellent teaching skills, experience, and interest, as this is a teaching position. Georgetown University values student success, achievement, equality, diversity, and support. An ideal candidate will encourage and actively support all of these elements. Candidates must be self-directed and independent, but also committed to being an active and valuable member of our Data Science team.  

With its location in Washington, D.C., Georgetown University provides opportunities to connect with government agencies as well as high-tech industries. The Data Science and Analytics Program maintains considerable and continuous relationships with local and non-local companies, offers regular seminars and career fairs, and promotes a strong sense of community among faculty and students. 

Georgetown attracts some of the very best students in the country and the world. The Georgetown University Graduate Data Science and Analytics Program provides students with rigorous training in computational, mathematical, and statistical methods to prepare them for careers in data science and analytics.

Required Qualifications

• Education: Candidates must possess a PhD in Computer Science, Mathematics, Statistics, Data Science, or a related field.
• Teaching and departmental collaboration: Our department is a highly collaborative environment, we are seeking a candidate that is a team player, and is interested in helping the department grow and increase its prestige. Candidates must possess both teaching experience and a clear interest in working with, supporting, and advising students. Candidates should be comfortable with novel course development, teaching both online and in person, and carrying out student support. Familiarity with the following tools is expected; Canvas and the Canvas API, collaborative course development via git, Github, and Quarto, course website development and deployment, and Github-classroom usage.
• We seek a candidate with expertise in at least three of the following domains.
• Big data and cloud computing: Proficiency in Big Data technologies (Hadoop, Spark, Hive, Pig), knowledge of distributed computing concepts, experience with cloud platforms (AWS, Azure, Google Cloud Platform), familiarity with cloud computing models (IaaS, PaaS, SaaS), understanding of data storage and management in the cloud, experience with data processing and ETL pipelines, proficiency in programming languages (Python, Java, Scala), knowledge of containerization and orchestration tools (Docker, Kubernetes), understanding of data security and compliance in the cloud, ability to design and deploy scalable data architectures. Familiarity with the following tools; AWS, Azure, linux, bash, ssh, Hadoop, Spark, MapReduce, etc.
• Data-visualization: Proficiency in data visualization tools , understanding of visualization principles and best practices, knowledge of human perception and visual cognition, experience in programming languages for visualization (Python with Matplotlib, Seaborn; R with ggplot2), ability to tell stories with data, understanding of different types of charts and their appropriate use, skills in data cleaning and preparation, knowledge of interactive visualization techniques, experience with web-based visualization tools, ability to teach design aesthetics and effective communication. Familiarity with the following tools; Tableau, Gephi, R/Shiny, R/leaflet, R/NetworkD3, R/ggplot2, seaborn, matplotlib, D3, Javascript, Bokeh, Plotly, etc.
• Data driven application development and deployment: Data science fundamentals, Application development frameworks (e.g., Shiny, Dash, Streamlit), Model building and evaluation, Data preprocessing and cleaning, Version control (e.g., Git), Containerization (e.g., Docker), Continuous integration/continuous deployment (CI/CD), Cloud platforms (e.g., AWS, Azure, Google Cloud), RESTful API development, Monitoring and logging, Security best practices, User authentication and authorization, Performance optimization, Scalability and load balancing, Frontend development basics (HTML, CSS, JavaScript), Data visualization techniques, Agile methodologies, Orchestration tools (e.g., Kubernetes), Infrastructure as Code (IaC) (e.g., Terraform, Ansible), Automation scripting (e.g., Python, Bash), Configuration management, Networking fundamentals, Collaboration and communication skills, Troubleshooting and debugging, System administration.
• Blockchain fundamentals:  Blockchain fundamentals, Smart contract development, Cryptography, Decentralized applications (dApps), Consensus algorithms, Ethereum and Solidity, Hyperledger frameworks, Blockchain architecture, Security best practices, Tokenomics, Distributed ledger technology, Peer-to-peer networking, Blockchain use cases and applications, Regulatory and compliance knowledge.
• Candidates must also have expertise in most of the following general domains:
• Programming & proficiency in relevant software tools: With an emphasis on standard Data Science tools including but not limited to, Python and R,  Jupyter, Excel, HTML/CSS/JS, web-publishing and dashboard creation, Quarto, Pandas, NumPy, SkLearn, NLTK, Matplotlib/Seaborn, and SciPy, SQL, Tensorflow, Keras, PyTorch, Ray, Dask, RL-Lib, Apache Spark, Tableau, Power BI, SAS, etc.
• General Mathematics: Single and multivariable calculus, linear algebra, algorithm implementations and numerical methods, basic and advanced statistics
• General Data Science Skills: Data munging (i.e data wrangling), gathering (including APIs), data cleaning and preparation, EDA, all components of the data science life cycle
• Data Storytelling: Expertise with communicating information from data, narratives, storytelling, visual narratives, decision science, etc.
• Machine Learning: Theory, algorithms, and applications. Classification and regression, Naive Bayes, decision trees & random forests, PCA, clustering, association rule mining, linear and logistic regression, etc.
• Deep Learning: Experience with deep learning as applied to NLP and computer vision. Familiarity with standard neural network paradigms (MLP, CNN, RNN, LSTM, VAE, Transformers) as well as experience with Keras, Tensorflow, and PyTorch. Added bonus would be familiarity with both traditional and deep reinforcement learning.  

The pay scale range for this position is $90,000 – 95,000. 

Submission Guidelines

In consideration of your interest in a non-tenure line faculty appointment with Georgetown University, you are requested to submit your updated CV, cover letter and list of at least three professional references. Please send one letter of reference with your application. We will request the other two letters if/as needed. You may receive a further request for additional information.

Please submit all application materials via Interfolio: apply.interfolio.com/157255

Need Assistance

If you are a qualified individual with a disability and need a reasonable accommodation for any part of the application and hiring process, please click here for more information, or contact the Office of Institutional Diversity, Equity, and Affirmative Action (IDEAA) at 202-687-4798 or ideaa@georgetown.edu.

EEO Statement

Georgetown University is an Equal Opportunity/Affirmative Action Employer fully dedicated to achieving a diverse faculty and staff.  All qualified applicants are encouraged to apply and will receive consideration for employment without regard to race, color, religion, national origin, age, sex (including pregnancy, gender identity and expression, and sexual orientation), disability status, protected veteran status, or any other characteristic protected by law.

About Georgetown University

Georgetown is a Catholic and Jesuit, student-centered research university. Established in 1789 in the spirit of the new republic, the University was founded on the principle that serious and sustained discourse among people of different faiths, cultures, and beliefs promotes intellectual, ethical, and spiritual understanding. We embody this principle in the diversity of our students, faculty, and staff, our commitment to justice and the common good, our intellectual openness, and our international character. An academic community dedicated to creating and communicating knowledge, Georgetown provides excellent undergraduate, graduate, and professional education.  Georgetown educates women and men to be reflective lifelong learners, to be responsible and active participants in civic life, and to live generously in service to others.