Data Analyst

We are seeking a highly skilled and motivated Data Services Analyst to join our dynamic team. As a Data Services Analyst, you will be responsible for analyzing healthcare data, generating insights, and providing data-driven solutions to improve operational efficiency, clinical outcomes, and patient care delivery. You will work closely with cross-functional teams to understand business requirements, design data models, and develop analytical solutions that meet the needs of our clients. Key Responsibilities: Collaborate with stakeholders to gather and understand business requirements related to healthcare data analytics. Design and develop data models, dashboards, and reports to visualize and communicate insights derived from healthcare data. Perform data analysis to identify trends, patterns, and anomalies in healthcare data sets. Develop and maintain data pipelines for data extraction, transformation, and loading (ETL) processes. Conduct quality assurance and validation of data to ensure accuracy, completeness, and consistency. Provide technical support and guidance to internal teams and clients on data-related issues and solutions. Stay updated on industry trends, best practices, and emerging technologies in healthcare data analytics. Qualifications: Bachelor's degree in Computer Science, Information Systems, Mathematics, Statistics, or a related field. Master's degree preferred. years of experience in healthcare data analytics, data engineering, or a related role. Proficiency in SQL, Python, R, or other programming languages for data analysis and manipulation. Experience with healthcare data standards and regulations (e.g., HL7, FHIR, HIPAA). Strong analytical and problem-solving skills with the ability to translate business requirements into technical solutions. Excellent communication and interpersonal skills with the ability to effectively collaborate with cross-functional teams. Experience with data visualization tools such as Tableau, Power BI, or Looker. Knowledge of cloud platforms (e.g., AWS, Azure, Google Cloud) and big data technologies (e.g., Hadoop, Spark) is a plus.