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Data Scientist
  • Python
  • Spark
  • SQL
  • Java
  • Machine Learning
  • Big Data
  • ggplot
  • Database
  • Data Mining
  • Modeling
  • Hadoop
  • MapReduce
  • Scala
  • C#
Los Angeles, CA
105 days ago
Advancement Services is an internal service group that coordinates and performs vital administrative, financial and technology services to the other UCLA External Affairs departments. This team facilitates and supports the broad range of its customers' activities through a variety of value-added services, including technical expertise and guidance for a wide range of projects and applications.

Under the supervision of the Director of Application Development, the Data Scientist will utilize analytical, statistical, and programming skills to collect, analyze and interpret large data sets, and will develop data-driven solutions to support digital marketing, fundraising, constituent relationship management, and leadership decision making for UCLA External Affairs (EA). As a mission critical position within the Application Development team, the Data Scientist will be primarily responsible for developing effective entity resolution model/s using big data analytics and incorporating vital machine learning technology to drive the success of the Grateful Patient program. The overall scope and complexity of the Grateful Patient program requires large-scale data integration between multiple UCLA databases including its patient database and External Affairs/Development's CRM.

The Data Scientist will have expertise in data mining/analysis methods including creating algorithms and running simulations to build and implement models. This individual will test the effectiveness of different courses of action and will work collaboratively with EA leadership to drive business results via data-based insights to improve our fundraising campaigns, donor prospecting, stewardship, alumni engagement, community outreach, and events. In addition, the Data Scientist will have the opportunity to work with technical staff to ensure EA's data lake on AWS is equipped with the right set of big data analytics tools, efficient data pipelines, and an infrastructure/platform that will support scalable machine learning models to be utilized by a wide range of production applications and systems.

Percentage of Time:

Shift Start:
8:00 am

Shift End:
5:00 pm

Qualifications for Position




1. Minimum of three to five years of experience manipulating data sets and building statistical models.


2. Experience in using statistical computer languages such as Python, R, SQL, etc. to manipulate data and draw insights from large data sets; coding knowledge and experience with several languages such as C#, Java, JavaScript.


3. Knowledge and experience in statistical and data mining techniques including text mining, social network analysis, etc. (E.g. GLM/Regression, Random Forest, Boosting, Decision Trees).


4. Experience creating and using advanced machine learning algorithms (E.g. Regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.) along with an understanding of their real-world advantages and drawbacks.


5. Knowledge of advanced statistical techniques and concepts such as regression, properties of distributions, statistical tests and proper usage, etc. and experience with applying these concepts in problem solving.


6. Experience working with and creating data architectures to include strong understanding of data governance principles.


7. Familiar with a variety of software/tools including AWS services in Analytics and Machine Learning; experience using cloud services such as RedShift, S3, Spark, etc.


8. Experience in working with relational databases as well as no-SQL databases; knowledge in SQL Server database design and T-SQL programming, with a mastery of SQL statements, stored procedures, triggers and functions, as well as data normalization best practices.


9. Experience analyzing data from third party providers: Google Analytics, Facebook Insights, Coremetics, Adwords, Crimson Hexagon, Site Catalyst, etc.


10. Experience with distributed data/computing tools: MapReduce, Hadoop, Hive, Spark, Gurobi, MySQL.


11. Experience in developing custom data models and algorithms as well as visualizing/presenting data for stakeholders using Periscope, Business objects, D3, ggplot, etc.


12. Detailed working knowledge of computer software tools, including workbench aids and automated systems for project management, data administration, data modeling, application controls and production documentation; a drive to learn and master new technologies and techniques.


13. Strong problem solving skills with an emphasis on software application and API development; a drive to learn and master new technologies and techniques.


14. Versatility working with various data sources and unit-specific databases.


15. Strong writing skills with the ability to write clear and detailed technical specifications and user documentation.


16. Excellent verbal communication and interpersonal skills to work effectively as a team member and diplomatically with staff; skill in leading work groups and meetings for the purpose of resolving divergent points of view on complex issues.


17. Highly organized and detail oriented with ability to complete multiple concurrent tasks, independently prioritize tasks and prepare project plans and schedules with only general guidelines from management.


18. Ability to independently perform functional analysis and systems research that is thorough, accurate, practical, identifies technical restraints, meets user requirements and maintains consistency with department planning strategies.


19. Master's or PhD in Statistics Mathematics, Computer Science or another quantitative field is preferred.


Additional Posting Information

Bargaining Unit:
99-Policy Covered

Application Deadline:

External Posting Date:

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