Senior/Lead Data Scientist

Що робити

Research and Development: Conduct research and stay up-to-date with the latest advancements in generative AI, deep learning, and related fields. Explore and experiment with different generative models, architectures, and algorithms to enhance our capabilities.
Model Development: Design, develop, and implement novel generative models tailored to specific use cases. Create and optimize deep neural networks, variational autoencoders (VAEs), generative adversarial networks (GANs), or other generative architectures to generate realistic and diverse synthetic data.
Data Preprocessing: Work closely with data engineers and domain experts to preprocess and clean large-scale datasets. Apply statistical techniques and data augmentation methods to ensure high-quality input data for training generative models.
Model Training and Evaluation: Train and fine-tune generative models using large-scale datasets, leveraging techniques such as transfer learning and unsupervised learning. Develop evaluation metrics and benchmarks to assess model performance and generate insights to guide model improvements.
Collaboration: Collaborate with cross-functional teams, including data scientists, software engineers, insurance experts, and experience designers, to integrate generative models into real-world applications. Provide technical guidance and support to ensure successful implementation and deployment of generative AI solutions.

Proven experience in developing and implementing generative models, such as GANs, VAEs, or deep generative models.
Strong proficiency in programming languages such as Python, with experience using deep learning frameworks such as TensorFlow or PyTorch.
Solid understanding of machine learning, deep learning, and statistical modeling concepts.
Experience working with large-scale datasets and preprocessing techniques.
Proficiency in data visualization and exploratory analysis tools.