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Office of Research Information Services (ORIS), a division of the Office of Research, coordinates, develops, and supports electronic research administration for faculty and staff at the University of Washington. Goals include:
Improve service to Principal Investigators (PIs) and research and administrative staff, enhance their ability to obtain funding, reduce their workload, and streamline the processing of their proposals.
Provide authorized individuals with convenient access to timely information on the status of proposals and awards.
Increase the efficiency of the research community to meet growing workload and compliance demands with limited resources.
Maintain the University of Washington's position as a leading public research University.
The University of Washington's Office of Research Information Services has an outstanding opportunity for a full time Data Analyst Lead.
The Data Analyst Lead for Decision Support Services (DSS) is responsible for data related projects and targeted initiatives aimed at facilitating organizational data sharing and reporting needs for the University of Washington (UW). This includes reports and data needs for units across the UW and data reports for state and federal requirements. The position supports researchers and research administrators in units within the Office of Research, data consumers in Dean's offices and other central administrative units. The Data Analyst Lead is the primary contact for sourcing research data into the UW Enterprise Data Warehouse, in alignment with UW Data Management Committee standards and policies. The work consists of data needs assessment, manipulation of quantitative data, report standardization, compilation of meta-data, and process definition.
Data originates from many sources including unit shadow systems. The Data Analyst Lead must be able to partner with units across campus to discern what is required in reporting and be able to uncover hidden data repositories and negotiate with units to standardize data warehousing and reporting. The Data Analyst Lead will be skilled at working with all levels of the UW and be able to discern when to provide detailed plans and strategies or when high level strategic presentations serve the purpose.
Supplying accurate data in an easy to retrieve method allows the UW to submit reports to state and federal agencies as required and for researchers to submit reports concerning awards. This ensures that the UW is compliant with rules and regulations, improves decision making, and allows reports to be run ad hoc with ease. DSS minimizes the cost of reporting, reduces risk and effort, and standardizes reporting.
Management of DSS team
Front-line supervision of a 3 person data analyst (DA) team, providing mentoring and coaching around best practices related to all aspects of the requirements, analysis, and development processes
Manage time and resource allocation of the DA team between multiple competing priorities, while considering the individual skills and interests of each DA
Provide a framework and direction for continued development of a standardized ORIS datamart, containing all ORIS system databases
Provide direction in the requirements development process for data within our ORIS software systems and the UW's larger Enterprise Data Warehouse effort
Provide functional leadership for data sourcing and development phase of the SDLC, including developing Minimal Marketable Features (MMFs) and data requirements stories
Develop standards and best practices for the integration and analysis of disparate data sources in the Research Administration domain area
In coordination with the DSS Assistant Director, continually refine the broader DSS strategy, in alignment with ORIS and Office of Research strategies
Advocate for growth and necessary training for the data analyst team
Represent the DA functional area in regular meetings with other functional Leads
Participate in on-going processes to define ORIS business processes and principles
Identify areas of improvement in the requirements development process and the overall development lifecycle process and work collaboratively to improve results
Project Management Responsibilities
Provide project management within the ORIS Federal Reporting Program
Understand and apply statutory reporting requirements from the federal and state government
Advocate for appropriate resources and prioritization to complete projects in a timely manner
Synthesize a variety of requirements relevant to Federal Reporting to develop project objectives in alignment to the larger program strategy
Work with management to ensure project deliverables are in alignment with the strategic vision for data
Work with ORIS team members to ensure project deadlines and deliverables are properly supported
Facilitate resolution of issues within the project decision making structure; determining appropriate escalation and resolution of issues within project structure
Act as a liaison by partnering with related offices and other product stakeholders that are a part of the grant life-cycle
Advanced analysis of research enterprise data
Assist and/or lead data analysis initiatives to evaluate data integrity, identify data gaps, and prototype data and analytical solutions.
Develop statistical packages, specifically using R, SPSS
Understand and apply a wide range of qualitative and quantitative research techniques and both univariate and multivariate statistical techniques
Work independently to uncover previously unknown insights in the data
Research analytical methods and tools
Source data from disparate data sources in order to assemble complete data solutions
Implement and assist in the development of data-driven business testing strategies
Streamline and enhance operational reporting
Ensure solutions deliver value to the UW research and research administration community
Define, map and model data sources
Develop, maintain, and promote data quality standards
Evaluate business requirements to model data and/or system requirements
Anticipate future needs of historical data in-line with current reporting needs
Work to develop, implement, and uphold change management processes related to daily operations and project work
Ensure translation of data into consistent, maintainable formats in preparation for the ETL process
Ensure stable, repeatable operational environment from daily ops to prod migration testing and acceptance
Convene, facilitate, and drive user groups with short-term charters meant to complete specific project deliverables
Effectively facilitate the communication and resolution of day to day and project level issues ensuring partner relationship are maintained and continue to improve
Assist in resolving business issues by analyzing data sets in order to illuminate meaningful relationships
Respond to data inquiries from various groups within the University, which may include ad hoc statistical and data mining analyses.
Ensure data sharing needs are met across various domains while still ensuring data access policies are applied and upheld
Communication, collaboration, and documentation
Bring transparency to day to day activities and project work
Present complete and concise recommendations to management when resolving difficult issues
Work effectively in a consensus driven, collaborative, team environment
Work with other analysts to develop and provide efficient data solutions, in line with project goals
Collaborate on designing new analytical reporting, products and features for our clients that enable data-driven decision making
Apply varied requirements gathering methods to ensure complete requirements elicitation
Bachelor's degree in a quantitative field such as Statistics, Applied Mathematics, Computer Science, or similar field and four to five years of related experience.
Strong collaboration skills and team player.
Demonstrated skill in working independently with databases to generate graphic and tabular reports, including building complex original queries, defining data elements, interpreting results, and documenting standard procedures for report designs.
Ability to research grant-related and higher education policies required, with an emphasis on strong analytical skills.
Excellent Knowledge of data warehousing concepts.
Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets.
Extensive knowledge of data design and tools required.
Strong background in statistics methodology, applications to business problems, and/or big data.
High proficiency of Microsoft SQL, Reporting Services, Visual Studio, and Visio.
Strong background in statistics, statistical analysis, and data visualization.
Strong working knowledge of data mining techniques.
Experience with survey analysis techniques, such as power analysis and determining response bias.
Experience with development processes like Agile/LEAN.
Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner.
Results driven personality with proven ability to work within a team environment to develop
solutions, provide tasks and ensure adherence to project goals and milestones.
Proven analytical and problem solving skills, including research design and methodology
A flexible analytic approach that allows for results at varying levels of precision.
Strong organizational skills.
Previous Experience in a technical lead role or similar role.
Outstanding verbal and written communication skills.
Equivalent education/experience will substitute for all minimum qualifications except when there are legal requirements, such as a license/certification/registration. MS in technical, statistical, or mathematic field.
Experience developing analytical solutions for the complete life cycle, with competing resources and priorities.
Experience with analytics, business intelligence, data visualization, distributed data warehousing and/or data mining systems, preferably with one or more Big Data or NoSQL technologies (Hadoop, Hive, Pig, HBase, Cassandra, MongoDB, etc.).
Demonstrated success interacting with diverse technical and non-technical groups, spanning all organizational levels.