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