The Data Scientist III leads and serves as the subject matter expert for data science projects and mentors junior data science team members. The employee will use large data sets and varied types of structured and unstructured data and apply a range of techniques including statistical, machine learning, and natural language processing, to discover, explore, and uncover, patterns and insights and distill them into readily consumable formats and visualizations. The Data Scientist III is responsible for turning data into actionable, data-driven insights that enhance the delivery of clinical care, operational performance and clinical decision-making.
Essential Responsibilities
Responsibilities listed in this section are core to the position. Inability to perform these responsibilities with or without an accommodation may result in disqualification from the position.
Lead data science projects from inception to completion, including planning, resource allocation, and stakeholder communication.
Utilize statistical techniques and machine learning algorithms to uncover patterns and trends within large datasets.
Design, build, and refine advanced machine learning models, including predictive, prescriptive, and diagnostic models to solve complex business problems, optimizing performance metrics.
Translate data insights into actionable strategies and recommendations for key business decisions.
Ensure data integrity and quality by establishing data governance practices and standards.
Work closely with cross-functional teams to understand business needs and align data science initiatives accordingly.
Guide and mentor junior data scientists on technical skills and best practices.
Effectively present complex data insights to both technical and non-technical audiences through clear visualizations and reports.
Analyze highly technical issues identified from the use are varying data sources.
Act as a storyteller, synthesizing knowledge from a variety of sources and able to clearly communicate complex topics to different audiences
General Responsibilities
Performs other duties as assigned.
Minimum Qualifications
Education Requirements: Bachelor's Degree required.
Experience Requirements:
5 or more years of experience using SQL, R or Python in analytics required.
Previous experience with data mining, analytical methods, data visualization, data storytelling and extracting value from large datasets required.
Experience with healthcare data use in Predictive Analytics preferred.
License/Certification/Registration Requirements: Epic certification/accreditation required within 6 months of hire or within 3 months of class completion including:
Cogito Fundamentals
Clarity Data Model
Caboodle Data Model
Access Data Model
Revenue Data Model
Clinical Data Model
Cognitive Computing Model
Additional epic classes as requested to support evolving business needs
Knowledge/Skills/Abilities Required:
Strong communication skills – Effective at working independently and in collaboration with other staff members. Capable of clearly presenting findings orally, in writing or through aspirations.
Expert analytical skills – Able to compare, contrast and validate work with keen attention to detail. Skilled in working with ‘real world’ data.
Strong problem-solving skills – Able to plan work, set clear direction, and coordinate own tasks in a fast-paced multidisciplinary environment. Expert at triaging issues, identifying data anomalies, and debugging software.
Advocate – actively identifies process improvements; drives changes professionally and confronts difficult circumstances in creative ways.
Strong experience with Python, R, SQL or others.
Strong experience with cloud data warehousing environments.
Expert understanding of analytical methodologies, and technical architecture.
Able to conduct analyses using Python or similar language.
Able to build dashboards using Tableau or similar BI tools.
Strong experience with Advanced Analytical Methodologies like: Regression Analysis, Clustering, Supervised Learning, Time Series, Decision Trees, Monte-Carlo Simulation, Naïve Bayes, Neural Networks, SVM’s, GIS, Attribution, Natural Language Processing, etc.
Skilled at partnering with non-technical stakeholders to turn vague business problems into crisp analytical projects.
Curious and self-motivated, thrive when working autonomously.