Lead Data Scientist

Memorial Hermann Health System; Town of Texas (WI); Hybrid; USD 95,000 - 130,000; Full time

Job summary

Memorial Hermann Health System is seeking a Data Science Lead to analyze complex data sets for decision making. This role requires leading cross-functional teams and providing data insights to address business problems.

A Bachelor’s Degree in a relevant field and 7 years of data science experience are required. Strong knowledge of statistical methods, SQL, and project management is essential for success in this fast-paced environment.

Qualifications

• 7 years of experience in data science required.
• Professional experience in a hospital setting preferred.
• Advanced statistical techniques and concepts knowledge.

Responsibilities

• Leads high-priority data science projects.
• Develops custom data models and algorithms.
• Provides technical supervision to other data scientists.

Skills

Data analysis

Statistical methods

Machine learning techniques

SQL database management

Project management

Communication skills

Education

Bachelor’s Degree in STEM field

Master’s Degree in Data Science

Tools

Statistical analysis tools

Job description

Job Summary

Leads the analysis of complex and unstructured data sets using advanced statistical methods for data‑driven decision making. Responsible for leading cross‑functional teams and providing in‑depth data insights for complex business problems. Manages engagement with internal customers on small and medium‑sized projects. Reports to the Manager of Data Science.

Minimum Qualifications

• Bachelor’s Degree in science, engineering, computer science, mathematics, statistics, or related STEM field (required)
• Master’s Degree in Data Science (preferred)
• Seven years of experience in data science (required)
• Professional experience in hospital setting, medical informatics, healthcare IT/finance/revenue cycle data management, or Electronic Health Record (EHR) data management (preferred)
• Business analytical skills (process flows, procedures, spreadsheets, modeling, etc.), technical expertise, mathematical skills and good understanding of design and architecture principles (required)
• Deep understanding of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real‑world advantages/drawbacks
• Proficient understanding of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications
• Ability to communicate, gather requirements and execute storytelling with data
• Advanced level knowledge of the data science project life cycle
• Proficient programming skills and experience with statistical analysis tools
• Proficiency in problem solving, analytical reasoning and decision‑making skills
• Proficiency in identifying and seeking needed information for problem/situation analysis
• Advanced experience in researching and resolving data issues with large, complex, incomplete data sources
• Strong project management skills, ability to work independently on multiple projects with competing priorities and commitment to meeting goals and deadlines
• Advanced understanding of SQL database management tools
• Exceptional analytical skills and ability to interpret results based on advanced statistical techniques
• Strong written and verbal communication skills in IT and business environments; ability to communicate with both technical and non‑technical audiences
• Ability to work under minimal supervision in a fast‑paced multidisciplinary environment
• Advanced knowledge of data science methods – time series forecasting, linear regression, A/B testing, statistical testing, clustering, etc.
• Superior customer service by delivering first‑rate work products and project management
• Strong ability to manage challenging client situations, troubleshoot and recommend solutions, and translate complex information for stakeholders

Principal Accountabilities

• Leads high‑priority projects that impact the organization.
• Leads complex issues and problems, and refers more complex issues to higher‑level staff.
• Provides technical supervision/mentoring to other data scientists and trains the broader audience on data science developments.
• Provides leadership, coaching, and/or mentoring to subordinate group.
• Develops custom data models and algorithms to apply to data sets.
• Develops and applies algorithms or models to key business metrics to improve operations or answer business questions.
• Provides findings and analysis for use in decision making.
• Performs research, analysis, and modeling on organizational data.
• Maintains existing models and evaluates their goodness of fit.
• Provides in‑depth data insights from structured and unstructured data for complex business problems using advanced analytics techniques, predictive modeling, data mining/visualization and pattern analysis tools.
• Develops and tests hypotheses and communicates findings in clear, precise, and actionable manner to project and leadership teams.
• Works closely with teams to identify, understand, and resolve data issues and improve efficiency, productivity and scalability of data processes.
• Assists with the evaluation of data science vendors and tools.
• Ensures safe care to patients, staff and visitors; adheres to all policies, procedures, and standards within budgetary specifications including time management, supply management, productivity and quality of service.
• Promotes individual professional growth and development by meeting requirements for mandatory/continuing education and skills competency; supports department‑based goals that contribute to the organization’s success, serves as preceptor, mentor and resource to less experienced staff.
• Demonstrates commitment to caring for every member of the community by creating compassionate and personalized experiences.
• Models service standards by providing safe, caring, personalized and efficient experiences to patients and colleagues.
• Other duties as assigned.