• Starts Jun 4
- As the world becomes increasingly more digitalised, the importance of data and the understanding of it grows day by day. Sage AI is a nimble team within Sage building the future of cloud business management by using artificial intelligence to turbocharge our users' productivity. The Sage AI team builds capabilities to help businesses make better decisions through data-powered insights.
- As a part of our team, you will be crafting machine learning solutions to help steer the direction of the entire company’s Data Science and Machine Learning effort. You will have chances to innovate, contribute and make an impact on the rapidly growing FinTech industry.
- You will participate in the design, development, delivery, and analysis of high-quality machine learning solutions that contribute to the success of Sage and contributes intelligence to its products. You will learn how to use cutting-edge ML/AI tools such as tensorflow/pytorch, sklearn, etc. as well as the tools that are used to run models in production – docker, kubernetes, AWS, etc.
- Core to the role, you will have passion and motivation for all things Data Science and Machine Learning, whilst appreciating that learning is a key part of the role, just as is the confidence to suggest recommendations and effectively communicate results to diverse groups and stakeholders.
- As part of this internship, you will pair with a dedicated mentor from Sage AI and gain hands on experience in all parts of the ML Development lifecycle in order to hone both your technical and professional skills.
- Innovation will be at the heart of this role, and as such you will continually demonstrate the sharing of new idea, suggest opportunities and better ways of working.
Area of Responsibilities
• Contribute to the data analysis and development of effective statistical models for segmentation, classification, optimisation, time series, etc.
• Design and implement model validation and performance metrics and build dashboards that help us track these metrics over time
• Present findings to the wider team and/or organisation
• Identify insights, suggest recommendations that influence the direction of the business
• Suggest improvements in the tools and techniques to help develop the team
- Skills, knowledge, and experience that will help you thrive in this role are: (desired, but not essential)
- Experience utilising statistical and machine learning technique either as part of a degree or personal project, including qualitative analysis (e.g., content analysis, phenomenology, hypothesis testing) and quantitative analysis techniques (e.g., clustering, regression, pattern recognition, descriptive and inferential statistics)
- Experience with SQL and relational databases
- Experience in presenting qualitative and quantitative data
- Experience in collaborating with individuals and/or groups
- Experience in complex problem solving
- To thrive in this role, you will need to be studying toward a degree in a quantitative discipline (applied mathematics, statistics, computer science, operations research, or related field)
You could also have:
- Experience as a Programmer - Python, Java, C#, or other language
- Solid mathematical and analytical reasoning fundamentals as demonstrated through your coursework or independent projects.