Senior Data Analyst

As a Senior Data Analyst, you will be responsible for collecting, analyzing, and interpreting large volumes of data to drive business strategies and decision-making. They are seeking a candidate with experience in using visualization tools such as Tableau or Power BI to present data in an intuitive and impactful manner. This role requires a strong analytical mindset, advanced technical skills, and the ability to collaborate effectively across departments.

Responsibilities:

• Collect, clean, and analyze large and complex data sets to identify trends, patterns, and insights.
• Develop and implement data-driven strategies to drive business growth and optimize operational efficiency.
• Create visually compelling dashboards, reports, and data visualizations using tools such as Tableau or Power BI.
• Collaborate with cross-functional teams to define data requirements, metrics, and KPIs aligned with business objectives.
• Present complex data findings and recommendations in a clear and concise manner to stakeholders at all levels.
• Perform advanced statistical analyses to uncover correlations, forecast trends, and predict outcomes.
• Identify data quality issues, implement data cleansing processes, and ensure data accuracy and integrity.
• Stay up to date with emerging trends and advancements in data analysis, visualization, and relevant technologies.
• Mentor and provide guidance to junior analysts in data analysis techniques and best practices.

Requirements:

• Bachelor's in a quantitative field such as Data Science, Statistics, Mathematics, Statistics or a related discipline.
• Minimum of 5 years of experience as a Data Analyst, with a focus on data analysis, visualization, and reporting.
• Proficiency in using visualization tools such as Tableau or Power BI to create interactive dashboards and reports.
• Strong SQL skills for data extraction, manipulation, and analysis.
• Advanced knowledge of data analysis techniques, statistical modeling, and predictive analytics.
• Experience with data cleansing, transformation, and validation.
• Excellent problem-solving skills and the ability to work with large and complex data sets.
• Strong communication skills, with the ability to effectively convey complex findings and recommendations to non-technical stakeholders.
• A high level of attention to detail and a commitment to data accuracy and integrity.
• Proven ability to work effectively both independently and in a team-oriented, collaborative environment.