Data Analyst

Introduction:

The candidate is a highly skilled Data Analyst with expertise in Excel, Power BI, Tableau, SQL, and Python. They have a strong background in transforming complex business data into actionable insights, enabling data-driven decision-making. Their experience includes developing automated data solutions, building ETL pipelines, and modeling data to enhance efficiency and real-time data availability. They have successfully created numerous dashboards and KPIs, working closely with cross-functional teams to optimize business performance. Their analytical skills have contributed to improving marketing ROI, increasing user engagement, and identifying key bottlenecks in customer journeys. They have also been involved in financial analysis, risk assessments, and compliance monitoring to ensure business stability. The candidate is experienced in mentoring interns, leading data-driven projects, and delivering strategic recommendations to stakeholders. Their ability to analyze customer behavior and transaction trends has resulted in improved sales and customer satisfaction. Additionally, they have strong communication and collaboration skills, making them an asset in data-driven organizations. They are passionate about learning, technology, and continuous improvement, always seeking innovative ways to extract meaningful insights from data. With certifications in Power BI and Tableau, along with hands-on experience in cloud services, Agile project management, and data visualization, they are well-equipped to tackle complex analytical challenges. Their ability to translate data into meaningful narratives, spot trends, and optimize business processes highlights their expertise in business intelligence and analytics.

Responsibilities:

• Develop and automate data analytics solutions using SQL, Python, and ETL pipelines.
• Design and build interactive dashboards in Power BI, Tableau, and Excel for business insights.
• Extract, transform, and model data to improve reporting efficiency and enable real-time analytics.
• Analyze marketing campaign performance to optimize ROI and identify key success factors.
• Conduct in-depth customer behavior and transaction trend analysis to enhance sales strategies.
• Define and implement key performance indicators (KPIs) for performance tracking and decision-making.
• Identify and resolve bottlenecks in customer journeys to improve conversion rates and user experience.
• Perform financial risk assessments, compliance checks, and portfolio analysis for regulatory adherence.
• Provide strategic recommendations based on data-driven insights to support business growth.
• Collaborate with cross-functional teams, including Marketing, Sales, IT, and Customer Experience.
• Improve customer support efficiency by analyzing service metrics and implementing process enhancements.
• Mentor and train interns and junior analysts on analytics projects and best practices.
• Utilize cloud services (AWS, GCP) for scalable data processing and analytics solutions.
• Apply Agile project management principles to deliver data-driven initiatives efficiently.
• Participate in data analytics competitions and continuously upskill through certifications and training.