Data Science Analyst I - Personalized Medicine

The Augmented Intelligence in Medicine and Science (AIMS) Laboratory is breaking new ground on a daily basis in applying data driven insights to improve the care of our patients. This highly innovated lab funded by a number of R01 and other NIH grants is seeking a highly qualified data scientist to help derive insights from real-world clinical data that can be used to improve clinical practice. The individual will be an active leader in a highly innovative lab applying cutting edge machine learning techniques to multi-modal electronic health record (EHR), waveform and genomic data to answer highly relevant clinical questions and deploy these models into clinical care. 

 

The clinical deep learning scientist will partner with an array of data savvy clinicians, researchers and students on multiple clinical research projects in the AIMS lab and broader Charles Bronfman Institute for Personalized Medicine (CBIPM). The AIMS lab has access to EHR data from millions of patients with a diverse range of backgrounds and clinical conditions using a variety of data science techniques and is part of the Mount Sinai Million Project that is actively enrolling and genotyping one million Mount Sinai Patients. The lab leverages state of the art infrastructure including a large on-premise high compute cluster with dedicated GPUs for the lab. This individual will have strong technical skills in the areas of data extraction and cleaning, deploying and developing advanced ML models, and interpreting the results of these tests.

1. Analyzes data requests using information technology, enrollment, claims, pharmacy, clinical, contract, medical management, financial, administrative and other corporate data from both modeled and disparate internal and external sources.

a. Works with departmental staff to identify requirements for reporting and / or business intelligence tools.

b. Identifies necessary data, data sources and methodologies.

c. Collects, organizes, integrates, analyzes and interprets data.

d. Leverages advanced statistical analysis methods to create insightful recommendations and conclusions that may be communicated to the stakeholder.

e. Identifies and addresses expected and unforeseen data complexities to mitigate their impact on the analytic outcome and associated business decisions. Works to improve data quality where possible within created analytical models. Feeds data quality issues back to IT or identified data stewards to facilitate creation of high quality metrics.

f. Develops and may present reports, analyses and findings to senior management and others as scheduled or requested.

2. Responsible for one or more of the following stakeholder groups:

a. Contracting and Commercialization May assist in the modeling and forecasting contract scenarios, measuring ongoing performance and identify trends in performance to inform our clinical or contracting staff to improve contract outcomes.

b. Care Management Helps to identify, understand and prioritize at-risk members in need of care management. Helps stratify our membership to optimally use resources to focus on the patients most in need, currently or in the future.

c. Medical Directors Helps to identify utilization trends and variations across the different categories of health care services to assist the Medical Directors to focus their efforts to maximize contract performance and clinical effectiveness.

d. Quality and Documentation Helps to link payer quality and documentation opportunities into operational analytic processes to maximize our quality scores, top line revenue and optimize the use of resources in concert with MS Health System contracts.

e. I.T. / High Performance Computing in any ongoing projects.

3. Acts as liaison/analyst for internal stakeholders, understands their needs and translates them into reporting and analytic solutions.

4. Effectively communicates with stakeholders and customers and ensures all requests are properly triaged, recorded and tracked.

5. Adheres to corporate standards for performance metrics, data collection, data integrity, query design, and reporting format to ensure high quality, meaningful analytic output.

6. Helps identify and understand data from internal and external sources for competitive, scenario and performance analyses, and financial modeling to gain member/provider insight into new and existing processes and business opportunities.

7. Works closely with IT on the ongoing improvement of Mount Sinais integrated data warehouse, driven by strategic and business needs, and designed to ensure data and reporting consistency throughout the organization.

8. Develops and maintains project work plans, including critical tasks, milestones, timelines, interdependencies and contingencies. Tracks and reports progress. Keeps stakeholders apprised of project status and implications for completion.