Responsibilities:

Lead the analysis of large datasets to identify trends, patterns, and correlations that can inform business strategies and decision-making.
Collaborate with cross-functional teams to define key performance indicators (KPIs) and develop dashboards, reports, and visualizations to track and communicate business performance.
Design and implement advanced statistical models and machine learning algorithms to solve business challenges and enhance predictive analytics capabilities.
Conduct thorough data validation, cleansing, and transformation to ensure data accuracy, integrity, and consistency.
Develop and maintain data pipelines and ETL processes to automate data extraction, transformation, and loading tasks.
Stay current with industry trends, emerging technologies, and best practices in data analysis, machine learning, and data visualization.
Provide mentorship and guidance to junior analysts, fostering a culture of continuous learning and professional development within the team.
Communicate findings and insights effectively to stakeholders at all levels of the organization through presentations, reports, and interactive visualizations.
Collaborate with IT teams to optimize database structures, data storage, and data access for efficient data management and analysis.
Identify opportunities for process improvement and innovation through data-driven analysis and experimentation.

Requirements:

Bachelor’s degree or higher in Computer Science, Statistics, Mathematics, Economics, or a related field.
Proven experience (5+ years) in data analysis, business intelligence, or a related role, with a focus on healthcare or retail industry preferred.
Advanced proficiency in SQL for querying and manipulating large datasets, along with experience working with relational databases (e.g., MySQL, PostgreSQL).
Strong programming skills in Python or R for data manipulation, statistical analysis, and machine learning.
Hands-on experience with data visualization tools such as Tableau, Power BI, or Matplotlib for creating interactive dashboards and reports.
Familiarity with cloud platforms (e.g., AWS, Google Cloud) and big data technologies (e.g., Hadoop, Spark) is a plus.
Excellent problem-solving skills and the ability to translate business requirements into analytical solutions.
Strong communication and interpersonal skills, with the ability to effectively collaborate with cross-functional teams and present complex findings to non-technical stakeholders.
Proven ability to work independently, prioritize tasks, and manage multiple projects simultaneously in a fast-paced environment.
A passion for data-driven decision-making and a commitment to driving continuous improvement and innovation within the organization.

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