Data Project Associate - University of Rochester

Responsibilities **General Purpose:** CHeT OVERVIEW The Center for Health + Technology (CHeT) at the University of Rochester aims to enable anyone anywhere to receive care and participate in research. We currently employ over 80 talented and diverse individuals to conduct unprecedented studies to evaluate new treatments and measures of disease. Over the past 30 years, CHeT has conducted over 100 studies and enrolled over 40,000 participants, leading to seven FDA-approved drugs for Parkinson’s disease, Huntington disease, and other neurological conditions. POSITION OVERVIEW As a CHeT Data Assistant, you will support and collaborate with study teams to build data structures and data flow components to capture, query, and report on clinical trial data according to sponsor and regulatory requirements (e.g. FDA). You will leverage the power of the data to develop workable proof-of-concept machine learning solutions. **Responsibilities:** Provide expert level support to data scientists on NIH projects with ability to act with little to no intervention from data scientists outside of assigning work Develop and deploy data science methodologies and algorithms at scale and establish robust processes to insure the stability, accuracy, reproducibility and overall quality of all algorithms, processes, and the results they produce Create dashboards and perform ad-hoc analyses to monitor and understand important product metrics Supervise and mentor interns within CHeT and external collaborators Lead weekly to monthly discussions on project progress with team. Disseminate results through presentations, abstracts, and manuscripts. Other duties as assigned **Qualifications:** + Bachelor’s in Data Science, Computer Science, Engineering, Mathematics, Statistics or an equivalent technical field. + Master’s degree (preferred) + 1 years of relevant experience or equivalent combination of education and experience. + Expert technical experience and possess expert knowledge of a scientific computing languages and techniques such as Linux, Python (including machine learning modules), R, relational database systems, video/image/signal processing, natural language processing, statistics or experimental design, Linear and Generalized Linear regression models including the ability to diagnose and correct problems or equivalent combination of education and experience + Candidate must have understanding of unsupervised and supervised machine learning approaches including clustering and classification techniques. + Candidate must have experience working with multiple data types including numerical, categorical, and count data and possess the ability to manage competing priorities in a dynamic and fast paced business like environment + Exceptional communication skills,including written communication, with meticulous attention to detail and the ability to drive impact by being able to interface with persons of varying technical backgrounds The University of Rochester is committed to fostering, cultivating, and preserving a culture of equity, diversity, and inclusion to advance the University’s mission to Learn, Discover, Heal, Create – and Make the World Ever Better. In support of our values and those of our society, the University is committed to not discriminating on the basis of age, color, disability, ethnicity, gender identity or expression, genetic information, marital status, military/veteran status, national origin, race, religion/creed, sex, sexual orientation, citizenship status, or any other status protected by law. This commitment extends to the administration of our policies, admissions, employment, access, and recruitment of candidates from underrepresented populations, veterans, and persons with disabilities consistent with these values and government contractor Affirmative Action obligations. nt with these values and government contractor Affirmative Action obligations. **How To Apply** All applicants must apply online. _EOE Minorities/Females/Protected Veterans/Disabled_ **Location:** School of Medicine & Dentistry **Full/Part Time:** Full-Time **Opening:** Full Time 40 hours Grade 052 Neuro-Ctr Health + Tech/CHet **Schedule:** 8 AM-5 PM; OCC Wkends