Data Analyst (225-830)

A Data Analyst is responsible for interpreting data and turning it into information which can offer ways to improve a business, thus affecting business decisions. They gather information from various sources and interpret patterns and trends to provide actionable insights for decision-makers. Analysts work with executives and other business leaders to identify opportunities for improvement, recommend actionable insights, and collaborate with teams to implement the changes. Additionally, Data Analysts are pivotal in ensuring data integrity and quality, reporting anomalies in data structures, and suggesting solutions. Their role is crucial in keeping the organization competitive and ahead of industry trends by making informed decisions based on data analytics.

Responsibilities

• Analyze complex datasets to identify trends, patterns, and actionable insights.
• Communicate key insights and findings to non-technical stakeholders clearly.
• Develop and maintain comprehensive dashboards to track performance metrics.
• Support data collection, cleaning, and data governance processes for quality assurance.
• Collaborate with cross-functional teams to understand analytics needs and requirements.
• Create detailed reports and presentations to summarize data findings for executives.
• Identify new analytics needs and support data-driven decision making horizontally.
• Perform data extraction using SQL and other database tools as required.
• Ensure data compliance with legal, regulatory, and organizational standards.
• Conduct A/B testing to evaluate the impact of interventions on business outcomes.
• Train team members on data literacy and data-driven insights for business growth.
• Continuously improve analytics processes for efficiency and effectiveness.

Requirements

• Bachelor's degree in Computer Science, Statistics, or a related field is required.
• Proven experience as a Data Analyst or in a similar analytical role.
• Strong proficiency with SQL, Excel, and other data manipulation tools.
• Excellent understanding of data modeling, data mining, and segmentation techniques.
• Ability to present complex information in a clear and concise manner.
• Experience with data visualization tools such as Tableau or Power BI is preferred.
• Strong problem-solving skills and the ability to think critically about data insights.
• Experience with statistical programming languages such as R or Python is advantageous.
• Good communication skills, both written and verbal, for stakeholder engagement.
• Detail-oriented mindset with a commitment to data quality and accuracy.