Working Location : Metropolis Tower 1
Working Days : Monday to Friday
Working Hours : 9.00am to 6.00pm
Salary : $6,000 to $8,000 per month
Contract Duration : 5 months (with option to extend)
What’s the Role?
As an AI Analyst, you must have the ability to translate a business question into AI solutions which will require you to have knowledge of machine learning, GenAI and a good grasp of software development. Next to the AI capabilities and experiences you should be able to clearly and effectively present findings to your colleagues in other areas of expertise and business stakeholders.
You will be responsible for the followings:
- Develop AI solutions to business challenges with business analysis.
- Write clean and maintainable production-level code, knowledge on: Python, Databricks, GIT, Azure, SQL.
- Enhance machine learning models on ad-hoc basis.
- Work closely with the customer and the Product Owner day-to-day.
- Work in a highly-collaborative, friendly Agile environment, participate in Ceremonies and Continuous Improvement activities.
- Document and explain the results of analysis or modelling to both a technical and non-technical audience.
- Learn new engineering practices, technologies and continuously improving our Agile practices.
What You Must Have:
- Degree in Computer Science, Information Systems, or a related field.
- Experience on AI projects and must have background in artificial intelligence, machine learning, or data science, with the ability to apply these techniques to generate insights and solutions for complex business problems.
- Familiarity with GenAI and the willingness to learn and contribute to its development and use cases.
- A practical common-sense approach to problem solving and attention to detail.
- A passion for and expertise in practicing AI to solve real-world customer problems.
- Preferred experience/ skillset:
- Trading experience e.g. Commodity Trading
- Statistical software packages such as Python
- Cloud environment like specifically Azure
- Experience in Agile working methodology.
- Excellent communication and interpersonal skills with good teamwork, and ability to collaborate effectively with stakeholders at all levels.
- Self-motivated and proactive, with a strong sense of ownership and accountability.
- Handle rapid onboarding on projects, understanding analytics goal and working with ill-defined datasets.
- Communicating technical jargon in plain English to colleagues within Data Science team and outside.
- Virtual working with network of colleagues located throughout the globe.
