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Form of workJob Description
Job Description:
Responsibilities:
Data Analysis and Interpretation:
Responsibilities:
Data Analysis and Interpretation:
- Conduct exploratory data analysis to Client trends, patterns, and anomalies.
- Develop and implement statistical models for predictive and prescriptive analysis.
- Interpret and communicate data-driven insights to non-technical stakeholders.
- Data Preparation and Cleaning:
- Clean and preprocess raw data to ensure accuracy and reliability.
- Work with large datasets from diverse sources and formats.
- Collaborate with data engineers to create and maintain data pipelines.
- Algorithm Development:
- Develop algorithms for solving complex business problems.
- Implement algorithms for pattern recognition, clustering, and classification.
- Collaborate with business analysts, data engineers, and other stakeholders to understand business requirements.
- Present findings and insights in a clear and understandable manner to both technical and non-technical audiences.
- Bachelor's degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Physics), master's degree in IT field, or equivalent experience in Data Science.
- Proven experience as a Data Scientist or similar role.
- Fluent in Structured Query Language (SQL).
- Experience with Tableau and Power BI.
- Proficiency in statistical analysis and data visualization tools.
- Excellent problem-solving and critical-thinking skills.
- Strong communication and collaboration skills.
- 5+ years working in an Analytics position for a large-scale IT system.
- Working knowledge of Healthcare Programs (i.e., Medicaid).
- An understanding of healthcare enterprise systems (including, but not limited to claims, finance, members, and providers), with the ability to understand and communicate from a business and technical perspective.
- Knowledge of big data technologies and tools.
- Holding industry-recognized data science certifications, for example:
- Certified Analytics Professional (CAP).
- IBM Data Science Professional Certificate.
- Microsoft Certified: Azure Data Scientist Associate.
- SAS Certified AI and Machine Learning Professional.
- SAS Certified Data Scientist.
- Experience with tools like ArcGIS, Toad, SAS, SPSS, and RStudio.
- Virtual interviews will be conducted through MS Teams. .
- After those two days, continuing training will be done virtually.
