Company Overview 

Imagine if we could match patients with the treatments that prove the most effective for them . . . 
GNS Healthcare applies a powerful form of AI called causal machine learning to predict which treatments and care management programs will work for patients, improving individual patient outcomes and the health of populations, while reducing the total cost of care. 

Headquartered in the biotechnology and health IT center of Cambridge, MA, our patented REFS™ technology is based on recent breakthroughs in causal machine learning and AI that transforms massive quantities of patient data into computer models of disease at molecular, patient, and health system levels. These computer models power up solutions, products, and services that health plans, biopharmaceutical companies, health systems, and patient foundations utilize to slow disease progression, reduce adverse events and hospitalization, and improve therapeutic effectiveness. Our platforms and solutions have been validated across more than 40 diseases including oncology, cardiovascular and metabolic diseases, autoimmune diseases, neurology, etc. and have appeared in over 50 peer-reviewed publications. 

Position Summary 

We are seeking a motivated database analyst with healthcare experience to join our team to help us deliver on the analysis, observational studies and support of our data pipeline. An ideal candidate has an in-depth understanding of multiple types (e.g. claims, EMR/HER, disease registry) and sources (e.g. Optum, Symphony) of real-world data (RWD). If you have a solid experience working with healthcare informatics, measures, code sets, ontologies, and data as well as the processes and technology to support ETL, we would love to meet with you. 

Responsibilities

• Assists team members with the design and development of RWD analyses and predictive models. 

• Support projects which include specific epidemiology, health outcomes and other observational studies to better understand disease natural history, prevalence, comorbidities, treatment patterns, and health and safety outcomes in ‘real world’ patient populations. 

• Lead the data onboarding and transformation processes for various source data. 

• Continuously improve control processes, ensuring data integrity, quality, standardization, and security throughout the ETL process. 

• Function as a healthcare data subject matter expert to support the design, development, testing, implementation, and support of clinical information and intelligence solutions. 

• Provide complete documentation and communication of all processes, methods, and results. 

• Support production solutions, the ongoing updates, and maintenance of our reference data sources. 

 
Qualifications

• Bachelor’s/Master’s Degree, in healthcare informatics, medically related field or computer/database related degree preferred. 

• Experience in healthcare informatics and hands-on experience with large, diverse healthcare data sets (e.g. medical, pharmacy claims, and lab results) 

• Strong understanding of multiple healthcare claims and electronic healthcare records database. 

• Must have strong SQL skills and ETL (e.g. Informatica, Kettle, SSIS) and/or workload automation software to streamline processes. 

• Experience using a scripting language (Python, R, Java, Scala, C++, C# and Bash/PowerShell) to automate processes and support proprietary software. Machine learning, R, and python skills highly preferred. 

• Experience with Cloud computing concepts such as Microsoft Azure or Amazon AWS (Ideally AWS tech including S3, Redshift, Glue) 

• Experience with database platforms (e.g. Amazon RedShift, Snowflake, Microsoft SQL Server, Oracle, PostgreSQL, or equivalent) 

• Experience using Git and working on shared code repositories

• Experience with claims/EHR data sources, industry standard measures and code sets (e.g. ICD-10 codes, ICD-9 codes, HCPCS codes, CPT codes, HEDIS metrics, ETGs, HCCs, DRGs, etc.) and publicly available sources (e.g. HCUP) 

• Experience exploring and analyzing data and/or scripting ETL processes using SQL and other tools. 

• Experience using Tableau or other in-app data visualization platforms 

Nice to Have Skills: 

• Background in statistics, biostatistics, public health, research design, health economics, or other related quantitative healthcare field. 

• Experience with backend web (API) development, Kubernetes, Docker and Tableau 

• Experience with data processing frameworks such as Apache Spark, Beam, Dataflow, Crunch, Scalding, Storm, Hive and BigQuery 

• Experience extracting data from REST APIs and parallel processing large datasets