Company Overview

Imagine if we could match patients with the treatments that prove the most effective for them . . . GNS Healthcare applies causal machine learning and simulation technology to predict which treatments and care management programs will work for which 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 technology is based on its MeasureBase™ data integration architecture and patented REFS™ (Reverse Engineering and Forward Simulation) causal inference and simulation AI engine. Health plans, bio-pharmaceutical companies, healthcare providers, foundations, academic medical centers, and self-insured employers use GNS’ cloud-based solutions to solve pressing and costly problems including those surrounding metabolic syndrome, medication adherence, end-of-life care, preterm birth, personalized care pathways in oncology, auto-immune diseases, and diabetes, new drug target discovery, patient stratification in clinical trials, and more. GNS solutions focus on reducing adverse events, slowing disease progression, and improving therapeutic effectiveness through precision matching that maximizes impact on individual patient health outcomes while reducing wasteful spending and downstream medical costs.

Position Summary

This internship allows the participant to learn some of the ropes of Product Management in a software company. You will work with product, ux, engineering, science, r&d teams to drive development of a machine learning platform and user-facing applications for biopharma. Your role’s focus is on supporting the definition, creation, and rollout of the product offering in conjunction with other supporting team members and company leadership. This is a great way to learn hands-on what defining new products is all about.

Responsibilities

• Work as part of Product Management team to scope out the key features in new product component releases, decide on the priority of functional features in GNS proprietary platform and applications.
• Maintain Jira backlog of features for the product component you are defining and work closely with development team to decide on the technical features to be tackled in sprints and product releases.
• Support creation of documentation for product, vignettes for training workshops.
•  Work closely with UX designer to bring key functionality along with seamless user experience to the users.
• Meet with users (both external customers and internal users) & collect their requests into functional specification documents.
• Create feature roadmap for the product component you are slated to lead.
• Create Proof of Concept prototypes in R/R-shiny

Requirements

• Working towards PhD or MS in computer science, bioinformatics or related fields with some coursework in life sciences/biology, statistics/biostatistics.
• Experience with R/R Shiny
• Drive and passion to build usable tools and applications to simplify machine learning concepts/statistical inference and create meaningful results for clinical users.
• Team player
• Good communicator and educator, able to communicate ideas to a diverse crowd.
• Some knowledge of one of the statistical programming languages such as R and Bioconductor desired.
• Experience working in Agile environment is useful but not required.
• Some experience with statistical inference and machine learning and data processing.
• Optional - basic understanding of molecular biology, pharmacology, medicine, or the pharmaceutical R&D process.
• Excellent written, oral and presentation communication skills.

Equal Employment Opportunity

GNS Healthcare provides equal employment opportunities to all employees and applicants for employment without regard to race, color, national origin, religion, sexual orientation, gender, gender identity or expression, age, veteran status, disability, or genetics. In addition to federal law requirements, GNS Healthcare complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities.