Data Reporting and Analytics Consultant II, Biostatistics, Epidemiology, SAS, R, Python

Dr. Paola Gilsanz’s research team is seeking an organized programmer analyst to join a large and dynamic research team supporting active field data collection and secondary data analyses studies of lifecourse risk and protective factors of late-life cognition and dementia. The programmer analyst will be part of a large team and is expected to work closely with the principal investigator and program managers. Their responsibilities will include: 1) supporting front-end operations of two field studies; 2) developing, enhancing, and maintaining SAS analytic datasets related to those two field studies; 3) performing advanced statistical analyses (e.g. longitudinal modeling of continuous and binary outcomes, time to event models) in a timely manner; 3) summarizing results of analyses in tables and graphics for reports and manuscripts; and 4) preparing sections of the manuscript or leading manuscripts for publication. As part of the Cognitive Heath Programming Team, the programmer analyst would also support the other programmer analyst on the team as needed.

Qualifications include: 1) Strong statistical analysis and consulting background; 2) Experience with creation, analytical manipulation, and interpretation of large databases required; 3) A minimum of 1 year of analytical consulting experience (experience with medical records strongly preferred; prior work with cognitive data a plus); 7) Strong analytic and critical thinking skills, writing skills, communication skills, consulting skills, and ability to work within a team; 8) Must be an independent self-starter.

• Pursues self-development and effective relationships with others by sharing resources, information, and knowledge with coworkers and customers; listening, responding to, and seeking performance feedback; acknowledging strengths and weaknesses; assessing and responding to the needs of others; and adapting to and learning from change, difficulties, and feedback.


• Completes work assignments by applying up-to-date knowledge in subject area to meet deadlines; following procedures and policies and applying data, and resources to support projects or initiatives; collaborating with others, often cross-functionally, to solve business problems; supporting the completion of priorities, deadlines, and expectations; communicating progress and information; identifying and recommending ways to address improvement opportunities when possible; and escalating  issues or risks as appropriate.


• Assists with data analysis interpretation by organizing and editing reports and presentations telling a compelling story to stakeholders to enable and influence decision making.


• Supports data-informed decisions under the guidance of more senior employees by working with clients to identify and clarify key business needs; assisting in the development of outcomes and process measures; translating business requirements; informing data/information needs and data collection methods; measuring the impact of business decisions on clients, customers, and/or members; working with clients and staff to identify opportunities and methods to improve efficiencies with analysis; supporting end-users; and documenting processes and deliverables.


• Assists with data and information gathering for targeted variables in an established systematic fashion by cleaning and organizing data; querying, merging, and extracting data across sources; completing routine data refresh and update; and providing user support and documentation.


• Supports data preparation for analytic efforts under the guidance  of more senior employees by cleaning data to ensure quality and accuracy based on provided guidelines; and consolidating data.


• Assists with the execution of creative data analytic approaches leading to actionable outcomes by organizing metrics to be analyzed and calculating algorithms and conducting basic analyses under the guidance of more senior employees, including descriptive statistics.


• Assists with the development, implementation, and automation of business and reporting solutions by creating summary statistics; organizing data reports, visualizations, and/or interactive Business Intelligence (BI) reports; identifying opportunities to improve exiting reporting solutions; and preparing documentation as appropriate.