Data Scientist I, Digital and Innovation

CommonSpirit Health was formed by the alignment of Catholic Health Initiatives (CHI) and Dignity Health. With more than 700 care sites across the U.S., from clinics and hospitals to home-based care and virtual care services, CommonSpirit is accessible to nearly one out of every four U.S. residents. Our world needs compassion like never before. Our communities need caring and our families need protection. With our combined resources, CommonSpirit is committed to building healthy communities, advocating for those who are poor and vulnerable, and innovating how and where healing can happen, both inside our hospitals and out in the community.

Job Summary / Purpose
A Data Scientist I is responsible for conducting data analysis to improve the delivery of healthcare through Digital and Marketing technologies. Primary duties include the application of standard statistical and visualization techniques to extract insights from data and participating in the development of Machine Learning (ML) models.  In addition to these statistical skills, this role is also proficient at integrating data from large disparate data sources into a homogenous data store.  A Data Scientist I works closely with clients, data stewards, project/program managers, and other IT teams to turn data into critical information and knowledge that can be used to make sound organizational decisions

 
Essential Key Job Responsibilities
·         Effectively identify and communicate insights from both structured and unstructured data using visualization and statistical software packages to enhance organizational decision making.

·         Utilize a variety of machine learning techniques to generate predictive models that can be used to inform digital product roadmaps, understand user behavior, and personalize the user experience.

·         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.

·         Work collaboratively with business stakeholders to identify high impact analyses and use advanced analytics and statistical methods to demonstrate value to the organization.

·         Create presentations and reports for business stakeholders that clearly and succinctly identify the impact and value demonstrated by a given analysis.

·         Have fluency with many disparate data sources and effectively communicate data needs and quality issues to guarantee a high standard of data governance and control.

·         Execute on multiple projects simultaneously while being cognizant of project priorities and established timelines.

Benefits Include: Benefits include Medical, Dental, Vision, Paid Time Off, Holidays, Retirement Program, Disability Plans, Tuition Reimbursement, Adoption Assistance, Employee Assistance Program (EAP), Discount Programs, Life Insurance Plans, Worker Compensation, Dress for Your Day Policy, Voluntary Benefits.

Compensation Range:  $36.96 to $48.05, hourly rates, annualized.

Required Education and Experience

• Bachelor’s degree in statistics, mathematics, computer science, life sciences, or data science.
• 1+ years’ experience in advanced analytics, model building, statistical modeling, optimization, and machine learning algorithms including supervised and unsupervised learning
• 2+ years’ experience with data mining tools, and designing and storing/retrieving data from relational database systems

Preferred Qualifications:

• Master’s or PhD in statistics, mathematics, computer science, life sciences, or data science
• Experience in Healthcare
• Required Licensure and Certifications

Required Minimum Knowledge, Skills, Abilities and Training
·         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. (Tableau, Qlik and PowerBI)

·         Knowledge of advanced statistical learning techniques including predictive modeling, clustering, and feature reduction

·         Solid foundation in statistical and mathematical concepts; knowledge of advanced mathematical concepts such as Calculus, Linear Algebra, Probability a plus

·         A strong passion for empirical research and for answering hard questions with data

·         Ability to code in one or more of the following languages/tools to process and generate insights from data: SQL, Python or R

·         Experience in using advanced Python libraries (PySpark, Pandas, SciPy, NumPy)

·         Knowledge of programming concepts that support computational efficiencies (parallelism, container-based code, Tensorflow)

·         Experience with Big Data programming and data storage (Hadoop, Pig, Hive, Azure, Spark)

·         Knowledge of designing and storing/retrieving data from knowledge graph data system

·         Experience preparing statistical work for presentation before large groups

·         Experience working with unstructured data (text, images, etc.)

·         Experience with Microsoft Office products (Word, Excel, PowerPoint)