Data Scientist I identifies business trends and problems through complex big data analysis. Interprets results from multiple sources using a variety of techniques, ranging from simple data aggregation via statistical analysis to complex data mining independently. Being a Data Scientist I designs, develops and implements the most valuable business solutions for the organization. Prepares big data, implements data models and develops database to support the business solutions. Additionally, Data Scientist I may require an advanced degree. Typically reports to a manager. The Data Scientist I work is closely managed. Works on projects/matters of limited complexity in a support role. To be a Data Scientist I typically requires 0-2 years of related experience.
Data Scientist Job Description Template
Our company is looking for a Data Scientist to join our team.
- Determine the suitability and feasibility of an analytical solution for a given commercial problem.
- Exposure to engineering real time decision platforms and systems;
- Predictive and financial modelling experience;
- Preferred knowledge of text analytics/dealing with unstructured data;
- Awareness of ethical and regulatory constraints in utilising various data sets;
- Be excited to apply your data science knowledge to develop meaningful & predictive features for the wider analytics community;
- Have a desire to work in an Agile environment – where we take it on, grow & value every voice;
- Understanding the use of data science to support marketing initiatives;
- Be flexible, adaptable to change and enjoy dynamic environments;
- Experience in managing technical data analysis work;
- Engineering principles such as data sourcing, cleansing, joining and ETL;
- Bachelor’s Degree in quantitative (Engineering, Maths, Economics, Science or IT);
- Data visualisation;
- Machine learning (supervised and unsupervised);
- Enjoy being hands-on and possess strong attention to detail;
- Understanding of statistical techniques and approaches and the application of these for customer event analysis.