As a Hospital IQ Senior Data Scientist, you will be at the forefront of the challenge to ensure we apply the best approaches to data analysis and research, machine learning, and model life cycles so that we can turn raw data from numerous hospital IT systems into actionable insights.
The ideal candidate will have a passion for continued learning, and be flexible, self-motivated and pro-active, curious and inquisitive.
This individual will be comfortable with and approachable when exploring a complex problem with others.
Design and implement machine learning models to power predictions used by hospitals to make real-time optimal operational decisions.
Oversee validation of predictive model accuracy and training data quality.
Shepherd predictive models and other data analysis techniques through the development process, from inception through production and to continuous validation.
Help guarantee statistical integrity and accuracy within the team, and take accountability for business and team performance.
Expand the capabilities of the Hospital IQ platform through identifying opportunities, developing innovative research projects, creating quick prototypes, prioritizing actionable, impactful insights, and inspiring the adoption of advanced data science across the business.
Effectively manage multiple small and / or medium-sized projects simultaneously and with minimal supervision, potentially including external support.
Develop, mentor, and incorporate work from more junior colleagues.
Keep informed of relevant trends and developments in Data Science and Healthcare, and improve competence by participating in educational activities.
Thrive and promote idea exchange within a highly collaborative environment as part of Hospital IQ’s remote team of data scientists, software engineers, and non-technical staff.
MINIMUM QUALIFICATIONS :
5+ years experience developing statistical and machine learning models and analyzing large, complex datasets, with a proven record of creative R&D that positively impacts the company.
Advanced degree in a quantitative field, or commensurate work experience.
Experience performing the full lifecycle of machine learning model development activities; including data engineering, feature development, validation, implementation / assessment, transitioning to a production environment, and performance maintenance.
Experience with project leadership overseeing a team of technical experts, with a demonstrated ability for time management and mentorship.
Expertise in Python (including Jupyter Notebooks, NumPy, Pandas, SciPy, scikit-learn and data visualization libraries), SQL, and Git.
Proven ability and desire to learn, master, and apply new software, technologies and techniques.
Exceptional written and verbal communication skills, including a proven ability to effectively communicate ideas and insights to both technical and non-technical teams.
PREFERRED QUALIFICATIONS :
Experience working with data from EHRs and other healthcare data systems.
Experience with time-series analysis, deep learning and / or NLP, MySQL databases, and with big data tools like Google Cloud ML Engine, etc.
Experience with Agile and Scrum methodologies.
Experience with Continuous Integration systems like Jenkins.
Experience with Docker.