Lead Data Scientist
Skilled professionals to join a wider team and contribute to projects under the PwC US. 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.
The team would be supporting the development of assets (e.g., plugins) to further drive the AI strategy and put it into practice.
Seniority:
Senior with 8+ years of relevant experience
Responsibilities:
• 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:
• 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, ...)
• Strong problem-solving skills and attention to detail.
• Good communication skills, fluent English.
Your work will be here and to this extent:
Start: as soon as possible.
The project duration is at least a year.
The work is full remote.
Time overlap is from 14:00 to 18:00.
For further information: