Airswift is an international workforce solutions provider within the energy, process and infrastructure industries. Airswift serves as a strategic partner to our clients, offering a turnkey workforce solution to capture and deliver the top talent needed to complete successful projects by aligning with the unique needs of our clients. With over 800 employees and 6,000 contractors operating in over 50 countries, our geographical reach and pool of talent available is unmatched in the industry
Airswift has been tasked by one of our major oil & gas clients to seek a Data Scientist to work within their facilities located in Singapore.
Day to day responsibilities:
- Develop, maintain and improve Advanced Analytics models.
- Research and develop new analytical techniques to generate actionable solutions oriented for the business
- Collect feedback from internal/external clients to improve analytical tools
- Interpret new challenges from internal/external clients to develop new analytical solutions for operational problems
- Commission models together with representatives from internal departments.
- Carry out any additional tasks related to the position assigned by the Project Lead.
Previous education and experience required:
- University degree and excellent academic record required;
- MSc or PhD level in Computer Science, Engineering, Statistics, Physics, Mathematics, Operations Research or equivalent technical field is desired.
- Experience in Computer Science, Engineering, Statistics, Physics, Mathematics, Operations Research or equivalent technical field;
- Proficiency in either R, SAS, StatsModels (Python), Scikit-learn (Python) or other statistical package;
- Programming skills in at least one of the following languages: R, Python, Scala, SQL;
- Different levels of experience in applying machine learning and data mining techniques to real problems with large amounts of data;
- Proven application of advanced analytical and statistical methods;
- Knowledge of distributed computing or NoSQL technologies;
- Experience in the commercial application of machine learning methods and algorithms
- Experience in working with large datasets and relational databases;
- Knowledge of agile software development process and familiarity with performance metric tools;
Only shortlisted candidates will be contacted.