Data Scientist

Job Description:
Tabula Rasa Health Care is looking for a Data Scientist to work with business stakeholders, IT, analysts and application developers to advance in-house data-science capabilities and develop solutions to business challenges. The Data Scientist will be responsible for using analytical, statistical, and programming skills to collect, analyze, and interpret data sets. This position requires that the Data Scientist have substantial expertise over a wide range of technical competencies including search, machine learning, programming, databases, reporting technologies and statistics, and can develop creative workable solutions for a wide range of internal customers.

Primary Functions:

• Design and implementation of self-service analytics tools
• Initiating data enrichment efforts including the supplementation of company data with third party sources when needed
• Guiding data collection procedures as needed to support the required analytic systems
• Contributing to the processing, cleansing, and verification of the integrity of data used for analysis
• Perform ad-hoc analysis and presentation of results
• Creating automated anomaly detection systems and constant tracking of its performance
• Working with key stakeholders to ensure integrity and proper integration for all sources of enterprise data
• Data mining using state-of-the-art methods
• Selecting features, building and optimizing classifiers using machine learning techniques
• Develop algorithms to support and drive discovery of clinical conditions and metrics based on healthcare claims data

Qualifications:

Education, Experience & Training:

• Bachelor?s degree in Computer Science, Bioinformatics or related field
• 10+ years? working in OLAP including experience in ?big-data? environments using columnar data stores and Hadoop.
• Prior experience designing and deploying self-service healthcare analytics environments across business, clinical, financial and research stakeholders
• Experience with healthcare data analytics including Medicare/Medicaid Claims analysis, working with healthcare stakeholders, and familiarity with healthcare coding standards including both ICD10 and SNOMED CT.
• Experience in validated system environments

Specific Skills:

• Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
• Experience with common data science toolkits, such as Jupyter, R, Weka, NumPy, etc
• Excellent communication skills, both written and verbal
• Experience with data visualisation tools, such as D3.js, Tableau, ggplot, etc.
• Exceptional database skills (both relational and noSQL)
• Excellent scripting and programming skills
• Good understanding of statistics including distributions, statistical testing, regression, etc.

Competencies:

• Overall competency in business and technology
• Excited & motivated to work with large datasets covering many members over multiple years
• Sense of urgency to attend to IT leadership demands
• Responsive and prompt communication
• Customer-service oriented
• Excellent time management
• Excellent verbal and written communication skills
• Self-motivated, team player, highly organized
• Attention to detail and accuracy of facts and documentation
• Ability to manage multiple priorities and work independently
• Ability to problem-solve and ability to follow through on tasks

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Requeriments :

• Technical Bachelor

Skills :

• Data Mining
• Machine Learning
• NoSQL
• Programing Skills
• Programming in R
• Statistics

Areas :

• Bioinformatics

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Additional Info:
Tabula Rasa Health Care? TRHC is a family of companies that leverages technology to improve healthcare. TRHC works with providers and insurers to identify multi-drug interactions and to reduce risk of medication-related problems. We have developed the first multi-drug interaction tool that identifies risk across a variety of safety factors and presents meaningful opportunities to mitigate that risk. This technology can be used to assess safety at the individual patient-level or to stratify medication risk at the population-level, and can be embedded within any EMR or other healthcare IT system.

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