Lead Data Scientist (Machine Learning) in Houston, TX

Lead Data Scientist (Machine Learning, Statistical Techniques, SQL, Data Sets, Cogito, AWS, Business Analytics, Project Lead) in Houston, TX

POSITION: Lead Data Scientist (Machine Learning, Statistical Techniques, SQL, Data Sets, Cogito, AWS, Business Analytics, Project Lead)
DURATION: Full-Time position
LOCATION: Houston, TX (onsite)
SALARY: Excellent Compensation with benefits
SKILLS: Data Science, Machine Learning Techniques, Statistical Techniques, SQL Database Management, Building Data Sets, Cogito, AWS, Business Analytics, Project Lead, Executive Presentation

DESCRIPTION:

MINIMUM QUALIFICATIONS:

• Bachelor s Degree in Computer Science or Engineering Required.
• Master s Degree in Data Science preferred.
• Seven (7) years of experience in data science is required
• Must have Cogito experience
• AWS Certification is a MUST
• Possesses deep understanding of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks) and their real-world advantages/drawbacks
• Proficient understanding of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage) and experience with applications
• 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
• Project Lead Experience
• Building Data Sets
• Presentation to Executives
• 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
• Advanced understanding of SQL database management tools
• Exceptional analytical skills and ability to understand and interpret results based on advanced statistical techniques
• Ability to communicate, gather requirements and execute storytelling with data
• 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
• Strong written and verbal communication skills in IT and business environments; ability to communicate to technical and non-technical audiences
• 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

ROLE:

• 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.
• Leads high priority projects that impact the organization.
• Leads complex issues and problems.
• Knowledge of advanced analytics techniques, predictive modeling, data mining/visualization and pattern analysis tools.
• 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.
• Promotes individual professional growth and development by meeting requirements for mandatory/continuing education and skills competency

===