Lead Data Scientist

For one our multinational clients based in Europe, we are currently looking for a Lead Data Scientist. The team would be supporting the development of assets (e.g., plugins) to further drive the AI strategy and put it into practice.

Details:

• Role: Lead Data Scientist
• Location: Remote role with minor travels (once per 3 months ) in Europe for 2-3 days for meetings.
• Working hours: 10-18 CET due to client location based in USA.
• Start: asap
• Duration: 6 months+ extension

Scope:

The long term goal is to deliver the firm's new strategy to tax solutions / automations. Ideal candidates would have a tax domain knowledge and tax tech experience, yet not a mandatory requisite for applicants.

• 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
• Lead a small data science team of ~4 people.

Requirements:

• Senior with 8+ years of relevant experience
• 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
• Practical exposure to GenAI projects and related frameworks (RAG apps, vector DBs, LangChain, LlamaIndex, agentic frameworks, ...)
• 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, ...)
• Leading skills and previous experience
• Strong problem-solving skills and attention to detail
• Good communication skills, fluent English