What does a data scientist do?
The Harvard Business Review deemed Data Scientists as the “sexiest job of the 21st century”.
Data science involves the application of various tools, data mining, statistical techniques, algorithms and machine learning principles to identify trends, patterns and insights from raw data. Data scientists extract meaning from data, uncover insights and identify opportunities to inform business decision making.
Building a data science capability has become a priority for many organisations due to the immense value big data can deliver. This has resulted in strong demand for skilled data scientists across a wide range of industries and professions.
Data scientist responsibilities
- Identifying relevant data sources for business needs
- Collecting structured and unstructured data
- Sourcing missing data
- Organising data in to usable formats
- Building predictive models
- Building machine learning algorithms
- Enhancing the data collection process
- Processing, cleansing & verifying of data
- Analysing data for trends and patterns and to find answers to specific questions
- Setting up data infrastructure
- Develop, implement and maintain databases
- Assess quality of data and remove or clean data
- Generating information and insights from data sets and identifying trends and patterns
- Preparing reports for executive and project teams
- Create visualisations of data
Who does a data scientist report to?
A data scientist may report directly to the leader of a project or a department e.g. CMO, or they may report to a Chief Data Officer or Head of Analytics in a larger data analytics team.
What skills does a data scientist need to have?
A good data analyst has a blend of technical and soft skills.
- Strong mathematical & numeracy skills
- Intermediate understanding of databases such as SQL Server, Oracle and SAP.
- Understanding of reporting & data visualisation tools such as Business Objects, PowerBi and Tableau.
- Understanding of ETL framework and ETL tools including Alteryx and Microsoft SSIS
- Digital marketing analytics tools including Google 360, Google Analytics, Google Tag Manager and Adobe Marketing Suite
- Excellent analytical skills - the ability to identify trends, patterns and insights from data
- Strong attention to detail
- Presentation skills – ability to write and speak clearly to easily communicate complex ideas in a way that is easy to understand
- Problem solving skills
- A good communicator with effective stakeholder management & conflict resolution skills.
What qualifications does a data scientist need?
Whist a degree is not essential, data analysts often have tertiary qualifications or a background in statistics, maths, economics or data science.
What does a data scientist career path look like?
The growth in demand for data analysts means there are a wealth of career paths on offer.
Data Analyst >> Senior Data Analyst >> Junior Data Scientist >> Data Scientist >> Head of Data
How much does a data scientist earn?
Data analysts can earn between $120k for entry level roles up to $200k for more senior positions.