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Tier-1 employer, common data-analyst title, and mid-level experience raise applicant competition.
Core data-analysis and visualization skills are highly transferable across industries.
Explicit senior-level experience brackets plus degree and data-skill requirements create moderate shortlisting strictness.
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Conduct comprehensive data analysis to extract actionable insights and support decision-making.
Explore, visualize, and analyze historical data to identify trends, forecast performance, and investigate data discrepancies.
Provide user training, support, and communicate findings through compelling data visualizations; ensure data accuracy and integrity in data projects.
Bachelor's degree or equivalent in Computer Science, MIS, Mathematics, Statistics, or similar discipline; Master's or PhD preferred.
Relevant work experience varies by seniority: 2 to 5 years in data analysis depending on level (Standard I to Senior II).
Fluency in English and proficiency in data modeling, visualization, and statistical knowledge are required.
Attention to detail and accuracy in data handling is mandatory.
Someone comfortable working with complex datasets to uncover patterns and forecast trends, with a strategic focus on accuracy and quality assurance.
Experienced in providing analytical support on data projects and communicating insights through visual storytelling.
Capable of training and supporting users on data analysis tools, suggesting an operational and mentorship oriented working style.