Description 
We are seeking an experienced candidate to join our team working at the intersection of healthcare and genomics. In this role, you will analyze health records and genetic data to drive discoveries that improve patient outcomes and advance precision medicine initiatives. 

Responsibilities 
Apply data mining, data modeling, natural language processing, and machine learning techniques to extract information from large structured and unstructured datasets from various sources 
Integrate genomic, clinical, epidemiological, and other research data to identify biomarkers, disease pathways, and potential therapeutic targets 
Develop and implement analytics applications that transform raw data into meaningful insights using data-oriented programming languages and visualization software 
Design and execute statistical analyses to validate findings and support research hypotheses 
Collaborate with cross-functional teams of clinicians, researchers, and other data scientists, and support team members in data projects for tools, methodologies, and best practices. 
Contribute to experimental design, grant writing, and manuscript preparation 
Create clear, compelling data visualizations to communicate complex findings to both technical and non-technical stakeholders 
Qualifications 
BA or BS degree minimum, in a relevant field of study; Masters degree preferred. Relevant degrees are Bioinformatics, Computational Biology, Genetics, Biostatistics, Computer Science or related field 
2 years of related experience 
Proficiency in Python, R, or similar programming languages for data analysis, and cloud computing platforms 
Experience with machine learning frameworks and statistical modeling tools 
Strong understanding of genomic data structures and healthcare data standards 
Demonstrated experience in academic or medical research settings