We are seeking a highly skilled and experienced Senior Data Scientist to join our dynamic team.
In this role, you will create rapid proofs of concept to test hypotheses about how emerging technologies can be applied to business use cases. We learn and explore at the forefront of Artificial Intelligence, Blockchain, Internet of Things, Robotics, Virtual Reality and Augmented Reality. The lab’s role is to generate prototypes, demos and learnings that our teams and clients can use when deciding how to apply and invest in emerging technologies.
The majority of the resources would be supporting the development of assets (e.g., plugins) to further drive our overall AI strategy across the firm. In addition to that, we have ongoing AI R&D initiatives that we’d look to leverage some of these roles to help us continue driving the initiatives.

REQUIREMENTS:

• Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
• Strong expertise with large scale Neural Networks, Deep Learning and Reinforcement Learning techniques.
• Experience with Probabilistic Graphical Modelling (Bayesian Networks, Markov Random Fields, Factor Graphs, …)
• Advanced knowledge of Python and machine learning frameworks (SciPy, Scikit-learn, TensorFlow, PyTorch, pyMC, pgmpy, …)
• Hands-on experience with one or more cloud computing platforms (Azure - preferred, AWS, GCP).
• Understanding of the whole ML lifecycle and experience with MLOps/DataOps.
• Experience with Probabilistic Graphical Modelling (Bayesian Networks, Markov Random Fields, Factor Graphs, …)
• Excellent problem-solving skills and ability to work independently in a fast-paced environment
• Strong communication skills and ability to collaborate effectively with team members and external partners, fluent English

• Development and training of transformer-based models for both text and images.
• Architect and oversee the entire model lifecycle, from data preparation, model design, training, development and validation to model deployment and monitoring.
• Collaborate with cross-functional teams, including data scientists, software engineers, and domain experts, to design and implement AI-driven solutions.
• Stay current with the latest advancements in AI and machine learning, integrating new techniques and technologies as appropriate.