We are seeking a highly skilled and experienced Senior Data Analyst to join our team. The successful candidate will be responsible for leading data analysis efforts, providing strategic insights, and driving data-driven decision-making across the organization. This role involves advanced data manipulation, complex analysis, and working closely with senior management and cross-functional teams.

Required Qualifications:

•  Bachelor’s degree in Statistics, Mathematics, Computer Science, Information Technology, or a related field.
• Master’s degree is preferred.
•  8-12 years of experience in a data analysis role, with a strong background in advanced data management, analysis, and visualization.

Technical Skills:

• Proficiency in data analysis tools and software, such as SQL, Excel, and advanced data visualization tools (e.g., Tableau, Power BI).
• Strong knowledge of statistical analysis, predictive modeling, and data mining techniques.
• Experience with database management systems (e.g., SQL Server, Oracle).
• Proficiency in programming languages such as Python or R.
• Familiarity with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure, Google Cloud) is a plus.
• Analytical Skills: Strong analytical and problem-solving skills, with the ability to work with complex datasets and derive meaningful insights.

Key Responsibilities:

• Advanced Data Analysis: Lead the analysis of large, complex datasets to extract actionable insights and support business strategies.
• Strategic Reporting: Develop and maintain advanced reports and dashboards to track key performance indicators (KPIs) and support strategic planning.
• Data Visualization: Create sophisticated visualizations to communicate complex data insights effectively to senior management and other stakeholders.
• Data Management: Ensure data integrity, accuracy, and consistency by implementing rigorous data validation and quality control processes.
• Requirements Gathering: Work with senior management and business units to understand their data needs and translate these into technical requirements and analytical solutions.
• Data Modeling: Design and maintain advanced data models to support various analytical and reporting needs.
• Collaboration: Collaborate with IT, business units, and other teams to ensure data alignment and consistency across the organization.
• Trend Analysis and Forecasting: Conduct trend analysis and predictive modeling to provide proactive insights and support long-term strategic planning.
• Ad hoc Analysis: Perform complex ad hoc analysis as required to support specific business initiatives and projects.
• Documentation: Document methodologies, processes, and findings. Maintain comprehensive records of data analysis activities.
• Mentorship: Mentor and guide junior data analysts, providing training and support to enhance their analytical skills and understanding.