Lead Data Scientist

Job Title:

Lead Data Scientist

Location:

Houston, TX (HYBRID)

Duration:
Direct Hire/Permanent position

Salary: $125k - $140k DOE

• 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

• Seven (7) years of experience in data science is required.
• Professional experience in a 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.

• 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…