Bachelor’s or Master’s degree in Data Science, Computer Science, Information Systems, or a related field.
Experience:
5+ years of experience in data analysis with strong proficiency in SQL, Python, and/or R.
Hands-on experience with database management systems (e.g., MySQL, PostgreSQL, SQL Server, Oracle).
Knowledge of data architecture principles and experience with data warehousing solutions (e.g., AWS Redshift, Snowflake).
Familiarity with data science techniques, including machine learning algorithms, data visualization, and predictive modeling.
Experience with data visualization tools (e.g., Tableau, Power BI, Looker).
Skills:
Strong proficiency in statistical analysis and data modeling.
Ability to optimize SQL queries and manage large datasets.
Understanding of database administration tasks such as backups, recovery, and security.
Solid knowledge of data governance, data quality, and best practices in database architecture.
Excellent communication skills with the ability to explain complex data insights to non-technical stakeholders.
Data Analysis and Reporting:
Analyze large datasets to identify trends, patterns, and insights to support decision-making.
Develop, maintain, and automate reports and dashboards for key business metrics.
Collaborate with stakeholders to define key performance indicators (KPIs) and provide data insights.
Data Science and Predictive Analytics:
Use statistical models and machine learning techniques to uncover patterns and predict future outcomes.
Develop predictive models and enhance business intelligence tools.