Data Analysis:
- Extract analyze and interpret large datasets to provide actionable insights for business decisionmaking.
- Utilize statistical techniques and data mining tools to identify trends patterns and anomalies.
- Data Visualization:
- Develop and maintain dashboards and reports using tools like Tableau Power BI or similar platforms.
- Present complex data in a clear and concise manner to stakeholders across various departments.
- Data Quality Assurance:
- Implement data validation processes to ensure accuracy consistency and reliability of data.
- Conduct regular data audits and address data quality issues promptly.
- Collaboration:
- Work closely with crossfunctional teams including IT marketing finance and product management to understand their data needs.
- Participate in global project meetings and contribute to strategic planning.
- Documentation:
- Create and maintain detailed documentation of data processes methodologies and analysis results.
- Ensure documentation is aligned with corporate standards and accessible to global teams.
- Continuous Improvement:
- Stay updated on emerging data technologies tools and industry trends.
- Proactively seek opportunities to enhance data processes performance and scalability.
- Agile Practices:
- Participate actively in agile development methodologies including sprint planning daily standups and retrospectives.
- Adapt to changing priorities and effectively manage time to meet project deadlines.
- Problem Solving:
- Analyze complex data issues and develop innovative solutions to address business needs.
- Utilize advanced analytics and data modeling techniques to enhance data reliability.
- Compliance and Security:
- Implement and enforce data security best practices in all aspects of data analysis.
- Ensure compliance with global data privacy standards and regulations including GDPR HIPAA and others.
Mentorship:
- For experienced candidates: Provide mentorship and guidance to junior analysts promoting their professional growth.
- For freshers: Engage in continuous learning and seek mentorship from senior team members to develop expertise.
Preferred Candidate Profile
- Educational Background:
- Bachelors or Masters degree in Data Science Statistics Computer Science or a related technical field from an accredited institution.
- Any Fresher Graduate can apply.
Experience:
- Freshers: Demonstrated understanding of data analysis through academic projects internships or relevant coursework.
- Experienced candidates: Proven experience as a Data Analyst in a corporate or MNC environment with a portfolio of successful projects.
- Proficiency in programming languages such as SQL Python or R.
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