Olive is healthcare’s first intelligent digital workforce and has been successfully deployed at numerous healthcare systems across the country. Olive helps streamline and automate the most high-volume, repetitive tasks so healthcare professionals can concentrate on their patients and solving healthcare’s most challenging problems. Olive’s promise to her customers is that she finds out where she can make an impact, onboards quickly, shows up to work everyday, does her job extremely well, and gets smarter over time.

Are you passionate about the use of advanced analytics methods to enable Olive to get smarter overtime while delivering value directly to health systems? As a Data Scientist, you will be responsible for designing and leading implementation of analytic solutions, including predictive modeling, machine learning, data visualization, insight tools development, and data infrastructure improvements. You will collaborate with analytic partners and business partners from product, customer success, data strategy, and infrastructure to develop effective solutions for our customers.

Great candidates for this position will have a passion for delivering business value throughout all phases of the analytics lifecycle and find fulfillment in enabling a data-driven business.

Responsibilities

• Work collaboratively with business stakeholders to identify high impact use cases that use advanced analytics and statistical techniques to demonstrate value to the organization
• Document projects including business objectives, data gathering and processing, detailed set of results and analytical metrics
• Develop fluency with many disparate data sources and effectively communicate data needs and quality issues to guarantee a high standard of data governance and control
• Readily query, transform, and combine data to address the needs of business stakeholders, and be able to communicate the limitations of working with large, and often messy, healthcare datasets
• Participate in the development, validation and delivery of algorithms, statistical models and reporting tools to solve moderately complex analytical problems
• Use data visualization techniques to effectively communicate analytical results and support business decisions
• Create presentations and reports for business stakeholders that clearly and succinctly identify the impact and value demonstrated by a given analysis.·
• Execute on multiple projects simultaneously while being cognizant of project priorities and established timelines.·
• Be a thought leader in the data organization, proactively identifying high-value analyses and helping to steer the direction of the team

• Bachelor Degree in Mathematics, Statistics, Computer Science, Physics, or in an Engineering or Sciences discipline or related degree
• Knowledge of standard statistical techniques (hypothesis testing, descriptive, significance testing) and ability to use statistical software to create visualizations that concisely convey correlations, trends, and distributions
• Ability to code in one or more of the following languages/tools to process and generate insights from data: SQL, R or Python (PySpark, Pandas, SciPy, NumPy)
• Experience with Agile tools, Jira, Trello, Pivotal Tracker, or related
• A strong passion for empirical research and for answering hard questions with data
• Solid understanding of data types, structures, and algorithms
• High degree of resourcefulness, flexibility, creative decision-making, and technical problem-solving abilities
• Strong and effective written and verbal interpersonal skills with the ability to tailor your message to your audience, including ability to work in a self-directed environment
• Able to develop process improvement plans that incorporate observations and key performance trends

Preferred Skills/Experience Nice to Have:

• Graduate degree in a mathematical, scientific, or engineering discipline
• Experience in analyzing healthcare or biomedical data
• Understanding of continuous Integration, testing, deployment and release methodologies
• Version control such as GIT, Subversion, Team Foundation
• Ability to understand large scale software and system architecture
• Knowledge of programming concepts that support computational efficiencies (parallelism, container-based code)