Two (2) years or more experience in data analytics

When looking for candidates with two or more years of experience in data analytics, consider the following key skills and qualifications: 1. **Technical Skills:** - Proficiency in data analytics tools such as Python, R, SQL, or Excel. - Experience with data visualization tools like Tableau, Power BI, or Looker. - Familiarity with data warehousing solutions (e.g., Amazon Redshift, Google BigQuery). 2. **Statistical Knowledge:** - Understanding of statistical methodologies and techniques, such as regression analysis, hypothesis testing, and A/B testing. 3. **Data Manipulation:** - Ability to clean, process, and transform raw data into actionable insights. - Experience with data extraction and ETL (Extract, Transform, Load) processes. 4. **Business Acumen:** - Ability to understand business needs and translate them into analytical solutions. - Experience working cross-functionally with different teams (e.g., marketing, finance). 5. **Project Experience:** - Involvement in analytics projects from inception to implementation. - Experience presenting findings and recommendations to stakeholders. 6. **Soft Skills:** - Strong problem-solving abilities. - Excellent communication skills, both verbal and written. - Ability to work independently and as part of a team. 7. **Certifications (if applicable):** - Relevant certifications such as Google Data Analytics, Microsoft Certified: Data Analyst Associate, or those from professional organizations. When evaluating candidates, consider conducting a practical assessment where they can demonstrate their analytical skills and problem-solving abilities in real-time. This can help in identifying individuals who not only possess the required technical knowledge but also the ability to apply it effectively within a business context.