Bring your big data analytics expertise to help UCLA engage with donors and fundraise for research, teaching and patient care.  As the Junior Data Scientist on UCLA’s Advancement Technology Services team, your analyses and solutions will support decision-making in core areas like fundraising, digital marketing, and constituent relationship management.  A key focus will be on large-scale data integration, including the patient database and fundraising CRM, to support the development and success of our Grateful Patient fundraising program.  

Partnering with the Associate Director of CRM and Data Projects and colleagues in our business units, your work as the data scientist will improve our ability to raise donations in important UCLA areas like healthcare research and patient care.  You will use your experience in data mining, distributed big data/computing tools, and in developing custom data models and algorithms to drive results.  Your work on the Advancement Technology Services team will ensure our data lake on AWS is equipped with the right set of big data analytics tools, efficient data pipelines, and an infrastructure to support scalable machine learning models used in a wide range of production applications and systems. As a valued member of our team, you will be part of a highly driven and specialized team that performs vital technology services. Within our innovative and supportive environment, you will be inspired and equipped to excel and grow professionally.

**Please note, this is a hybrid position. UCLA External Affairs is unable to offer visa sponsorship.**

1.   Minimum of three years of experience using analytical, statistical, and programming skills to collect, analyze and interpret large data sets, and developing data-driven solutions is preferred.  

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

4.   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. 

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

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

7.   Experience in developing custom data models and algorithms as well as visualizing/presenting data for stakeholders using D3, QuickSight, Tableau, etc. 

8.   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. 

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

10. 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. 

11. Strong critical thinking and problem solving skills with an emphasis on software application and API development; ability to manage complex information, assess issues and develop and implement effective solutions; a drive to learn and master new technologies and techniques. 

12. Proven ability to serve as a technical resource providing advice and counsel on business intelligence issues. 

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

14. 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. 

15. 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.  

16. 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. 

17. Ability to work evenings and/or weekends as needed. 

18. Master’s degree in Statistics Mathematics, Computer Science or another quantitative field is preferred. 

Employment is contingent upon completion of a satisfactory background check. 

The University of California is an Equal Opportunity/Affirmative Action Employer advancing inclusive excellence. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories covered by the UC nondiscrimination policy.

Bring your big data analytics expertise to help UCLA engage with donors and fundraise for research, teaching and patient care.  As the Junior Data Scientist on UCLA’s Advancement Technology Services team, your analyses and solutions will support decision-making in core areas like fundraising, digital marketing, and constituent relationship management.  A key focus will be on large-scale data integration, including the patient database and fundraising CRM, to support the development and success of our Grateful Patient fundraising program.  

Partnering with the Associate Director of CRM and Data Projects and colleagues in our business units, your work as the data scientist will improve our ability to raise donations in important UCLA areas like healthcare research and patient care.  You will use your experience in data mining, distributed big data/computing tools, and in developing custom data models and algorithms to drive results.  Your work on the Advancement Technology Services team will ensure our data lake on AWS is equipped with the right set of big data analytics tools, efficient data pipelines, and an infrastructure to support scalable machine learning models used in a wide range of production applications and systems. As a valued member of our team, you will be part of a highly driven and specialized team that performs vital technology services. Within our innovative and supportive environment, you will be inspired and equipped to excel and grow professionally.

**Please note, this is a hybrid position. UCLA External Affairs is unable to offer visa sponsorship.**

1.   Minimum of three years of experience using analytical, statistical, and programming skills to collect, analyze and interpret large data sets, and developing data-driven solutions is preferred.  

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

4.   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. 

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

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

7.   Experience in developing custom data models and algorithms as well as visualizing/presenting data for stakeholders using D3, QuickSight, Tableau, etc. 

8.   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. 

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

10. 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. 

11. Strong critical thinking and problem solving skills with an emphasis on software application and API development; ability to manage complex information, assess issues and develop and implement effective solutions; a drive to learn and master new technologies and techniques. 

12. Proven ability to serve as a technical resource providing advice and counsel on business intelligence issues. 

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

14. 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. 

15. 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.  

16. 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. 

17. Ability to work evenings and/or weekends as needed. 

18. Master’s degree in Statistics Mathematics, Computer Science or another quantitative field is preferred. 

Employment is contingent upon completion of a satisfactory background check. 

The University of California is an Equal Opportunity/Affirmative Action Employer advancing inclusive excellence. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories covered by the UC nondiscrimination policy.