Lead Data Scientist

Must-Haves

1 Project Lead Experience

2 Building Data Sets

3 Presenting to A-C level executives

4 Must have Cogito experience

5 AWS Certification is a MUST

MINIMUM QUALIFICATIONS

Education: Bachelor's Degree in science, engineering, computer science, mathematics, statistics, or related STEM field required. Master's Degree in Data Science preferred.

Licenses/Certifications: (None)

Experience / Knowledge / Skills:

Seven (7) years of experience in data science is required

Professional experience in hospital setting, medical informatics, healthcare information technology/finance/revenue cycle data management, or Electronic Health Record (EHR) data management is preferred

Business analytical skills (process flows, procedures, spreadsheets, modeling, etc.), technical expertise, mathematical skills and good understanding of design and architecture principles are required

Possesses deep understanding of a variety 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

Possesses advanced level knowledge of the data science project life cycle

Proficient programming skills in addition to a working knowledge and experience of statistical analysis tools

Demonstrates proficiency in problem solving, analytical reasoning and decision-making skills

Demonstrates proficiency in identifying and seeking needed information to perform problem/situation analysis

Advanced level of understanding and experience in researching and resolving data issues with a logical, instinctive, and problem-solving mentality working with large, complex and incomplete sources

Exhibits strong project management skills, with an ability to work independently on multiple projects with competing priorities and a strong commitment to meeting goals and deadlines

Advanced understanding of SQL database management tools

Exceptional analytical skills and ability to understand and interpret results based on advanced statistical techniques

Strong written and verbal communication skills in IT and business environments; ability to communicate to 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 in the form of first-rate work products and project management

Strong ability to manage challenging client situations

Strong ability to troubleshoot and recommend solutions

Strong ability to translate complex information for a wide range of 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 with the goal of improving operations or answering 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 through use of 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 Memorial Hermann 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 which contribute to the success of the organization; serves as preceptor, mentor and resource to less experienced staff.

Demonstrates commitment to caring for every member of our community by creating compassionate and personalized experiences. Models Memorial Hermann's service standards by providing safe, caring, personalized and efficient experiences to patients and colleagues.

Other duties as assigned.