Associate Director, Data Scientist
# of Openings:
As part of University Advancement Data
Strategy and Innovation team, the Data Scientist’s role is to turn
data into tactical information and knowledge by applying
statistical, algorithmic, mining and visualization techniques. Data
Strategy and Innovation plays a critical strategic role within
Advancement, providing the analytical framework, data architecture,
application development and tools for data-driven decision making,
as well as predictive analytics, that can be used by all levels of
The person in this role should be a
creative thinker and propose innovative ways to look at problems
and utilize data that can be used to make sound organizational
decisions. The Data Scientist will need to be able to present their
findings to the business by exposing their assumptions and
validation work in a way that can be easily understood by their
business counterparts. In addition, this position will serve as a
liaison to other teams within University Advancement – acting as a
technical lead and driving strategic planning to successfully
execute analytics strategies and solutions in support of the
University fundraising and engagement operation.
Princeton University Advancement works to
inform, inspire, and involve Princeton’s global community of
alumni, parents, and friends in ways that enable the University to
fulfill its mission of advancing learning through scholarship,
research, and teaching to serve humanity.
Statistical Modeling and Technical
Communication, Mentoring and Analytics
- Utilizing a combination of business focus, strong analytical
and problem-solving skills and programming knowledge, drive new
innovations and data exploration.
- Develop recommendation engines or automated lead scoring
systems to drive our prospect management strategy and marketing
segmentation, utilizing machine learning techniques.
- Work with structured data and drive innovation in unstructured
data architecture and analysis.
- Work with statistical programming language, like R or Python,
and database querying language like PL/SQL.
- Utilize innovative approaches to drive knowledge, incorporate
and promote a big data environment.
- Identify what data is available and relevant, including
internal and external data sources, leveraging new data collection
processes such as social media and web analytics.
Best Practices & Strategy
- Work with business users to define desired outcomes and
business requirements of analyses, data visualization and other
- Provide expertise on mathematical concepts for broader applied
analytics and inspire the adoption of advanced analytics and data
science across the Advancement Office.
- Describe findings or the way techniques work to audiences, both
technical and non-technical, effectively using presentation tools
such as data visualization, PowerPoint and documentation to drive
strategic decision making and understanding of business analytics
at all levels of the organization.
- Assist in addressing daily operational questions as needed,
identify critical process improvement areas and collaborate in
developing procedures and solutions for enhancing a high level of
- Working closely with Data Strategy and Innovation team members,
conceive of and contribute to strategies and best practices in
maintaining a comprehensive, reliable, and innovative data
- Review and recommend use of new technologies, vendor services
and information sources. Keep abreast of news and relevant industry
trends in support of the Office of Advancement.
- Develop and maintain proficiency in using advanced analytic and
database tools, internet resources, in-house data, and other
- Bachelor’s Degree and five to ten years of professional
experience required in an analytical or information specialist role
within an academic, nonprofit, corporate or consulting
- Deep understanding of statistical and predictive modeling
concepts, machine-learning approaches, clustering and
classification techniques, and recommendation and optimization
- Keen desire to solve business problems, and to find patterns
and insights within structured and unstructured data.
- Expert in analyzing large, complex, multi-dimensional datasets
with a variety of tools.
- Accomplished in the use of statistical analysis environments
such as R, MATLAB, SPSS or SAS.
- Experience with BI tools such as Tableau.
- Having a good understanding of relational databases, warehouse
design and architecture principles.
- Familiarity with big data frameworks (e.g., such as Hadoop,
- Good scripting and programming skills (e.g. familiarity with
SQL, Python, Java).
- Strong foundation in statistical, mathematical, predictive
modeling as well as business strategy skills to build the
algorithms necessary to ask the right questions and find effective
- Familiar with disciplines such as: natural language processing,
machine learning, conceptual modelling, statistical analysis,
predictive modeling and hypothesis testing.
- Able to create examples, prototypes, demonstrations to help
management better understand the work.
- Able to work autonomously.
- Proficiency at planning and setting meaningful objectives to
meet office goals. Ability to articulate and promote goals and
implement strategic plans.
- Strong interpersonal skills; as well as strong initiative and
self-motivation and the ability to work both independently and
manage teams within a customer-service oriented environment.
- Excellent written/oral/interpersonal communication skills in
order to: identify and articulate business challenges, project
objectives, and analytical approach.
- Organizational skills to handle several projects
simultaneously, accommodate shifting priorities, and meet
- Ability to maintain strict confidentiality and handle sensitive
information and material in a discretionary manner.
- Commitment to University Advancement’s mission to inform,
involve, and inspire Princeton’s global community of alumni and
friends, and adhering to its guiding principles of High
Performance, Innovation, Civility, and Collaboration.
- Knowledge of Princeton’s mission.
- Experience in higher education.
- Advanced degree in areas such as operations research, applied
statistics, data mining, machine learning, or a related
- Understanding of philanthropy (mission, practice, trends) and
fundraising practices (the development cycle, prospect management
policies and practices)
Princeton University is an Equal
Opportunity/Affirmative Action Employer and all qualified
applicants will receive consideration for employment without regard
to age, race, color, religion, sex, sexual orientation, gender
identity or expression, national origin, disability status,
protected veteran status, or any other characteristic protected by
law. EEO IS THE LAW