Roles & Responsibilities:

• Apply analytical theory to real-world problems on dynamic datasets

• Be hands-on in identifying problems in data and improving the quality of data using tools and

data labeling techniques

• Define quality metrics for the data and model performance

• Work in tandem with Machine Learning Developers to build and improve the tools to train, monitor and analyze model performance and data quality

• Identify areas in which more data could be collected and used to train the models

• Work with designers on collecting user data for training models purposes

• Work with other teams to understand the opportunities and constraints of existing data in the

context of ML and predictive modelling

• Propose technical solutions and strategies to business challenges in a self-driven environment

• Develop statistical models and algorithms for integration with our product

• Provide input into future data science strategy and product development

• Test, evaluate and improve the analytical results on live systems Demonstrate a strong

commitment to Excellence

Qualifications:

• Minimum 6 months of experience in the field of Data Science

• Experienced with multiple ML techniques such as deep neural networks, transformers and recommend-er models, as well as python ML libraries such as TensorFlow, PyTorch and sklearn

• Equipped with programming skills to self-sufficiently manipulate, analyse, synthesise, and visualize data in e.g. matplotlib, plotly, bokeh, pandas

• Experienced in the design and usage of relational databases (SQL, PostgreSQL)

• Experienced with testing frameworks (e.g. PyTest)

• Experienced with Docker containers in the context of training and deploying ML models