Certsys

Analyst

• Collect data from multiple sources, whether from databases or via data collection tools;
• Data cleaning and preparation: process raw data to ensure it is clean, consistent, and ready for analysis. At this stage, remove any duplicate, corrupted, or blank records that could distort analysis;
• Exploratory Data Analysis (EDA): perform exploratory analyses to understand data distributions and identify patterns and/or outliers that may indicate initial trends;
• Report and dashboard development: create visual reports and dashboards using Certsys tools and/or client-provided tools that highlight key insights identified during collection, cleaning, and EDA;
• Data modeling: actively participate in designing data models and database structures that support the organization’s analytical needs;
• Statistical analysis: apply basic statistical techniques to understand relationships between variables, perform hypothesis testing, and conduct comparative analyses based on business rules;
• Team collaboration: work with business teams, data scientists, and other professionals to gather analytical requirements and translate them into solutions;
• Understanding business objectives: maintain a solid understanding of the organization’s business goals to ensure data analysis is aligned with company objectives;
• Technical skill development: continuously improve technical skills, including programming languages such as SQL, Python, or R, and the latest data analysis tools;
• Communication of results: effectively communicate data analysis results to technical and non-technical stakeholders, ensuring insights are actionable and can influence business decisions;
• Identify opportunities to improve business processes based on data analysis findings.

Mid-Level Data Analyst

Administration

• Keep data models and logical and physical structures up to date;
• Ensure consistency, quality and governance of data and metadata;
• Participate in the evaluation and implementation of data-related automation solutions;
• Monitor the implementation of data models and the quality of databases;
• Work with BI, Big Data, data integration, metrics and dashboards;
• Support performance analysis and very large database (VLDB) environments.

Mid-Level Data Analyst

Data Administrator