Data Scientist

The ideal candidate will have a strong background in statistical analysis, machine learning, and data modeling. The Data Scientist will play a key role in extracting valuable insights from our data, contributing to policy decision-making processes, and developing innovative solutions to complex problems.

Primary Responsibilities :

• Data Analysis and Interpretation:
• Conduct exploratory data analysis to discover 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.
• Collaboration and Communication:
• 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.

Required Qualifications:

• 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.

Preferred Qualifications:

• 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, 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:

1. Certified Analytics Professional (CAP)
2. IBM Data Science Professional Certificate
3. Microsoft Certified: Azure Data Scientist Associate
4. SAS Certified AI and Machine Learning Professional
5. SAS Certified Data Scientist

• Experience with tools like ArcGIS, Toad, SAS, SPSS, and RStudio