The Data Analyst (DA) turns data into information and information into insights which can offer ways to improve business, thus affecting business decisions, gathering information from various sources and interpret both patterns and trends.
The DA is primarily responsible for extracting and analysing relevant data from existing systems, designing reports and delivering thoughtful, clear and concise presentations on the results of analysis to management to advance or improve productivity, efficiency, quality outcomes and achieve business/organizational goals.
The DA works independently on complex analytical projects and collaboratively with various stakeholders, managers and executives, in order to collect their needs and find the better ways to satisfies them. The DA will report back what has been found to the wider business/relevant colleagues, defining the useful subset of information and by providing it with the right representation forms.
The main tasks will be:
- Collecting and interpreting data
- Use statistical methods to analyse data and generate useful business reports
- Reporting the results back to the relevant members of the business
- Identifying patterns and trends in data sets
- Working alongside teams within the business or the management team to establish business needs
- Defining new data collection and analysis processes
- Define the useful information subset and the right representation forms
It is required:
- Master’s Degree in Computer Science, Mathematics, Statistics or another quantitative field
- Experience in data models and reporting packages, databases, programming
- Strong verbal and written communication skills
- An analytical mind and inclination for problem-solving
- Attention to detail
- Ability to write comprehensive reports
- A drive to learn and master new technologies and techniques.
- Technical expertise regarding data models, database design development, data mining and segmentation techniques
- Experience using statistical packages for analysing datasets
- Experience querying databases and using statistical computer languages: R, Python, SQL, etc.