Senior Data Scientist
We invite applications for the position of Senior Data Scientist, responsible for designing, developing, and deploying advanced AI and machine learning solutions to drive business value.
Responsibilities
- Stay up to date with the latest advancements in generative AI, general Data Science and machine learning frameworks, and their applications across industries
- Design, build, and deploy scalable machine learning models and pipelines in production environments
- Perform advanced statistical modeling and data analysis to identify trends, patterns, and actionable insights
- Knowledge of SQL-like and NoSQL databases
- Document technical solutions, model architectures, and data flows to ensure transparency and maintainability
- Monitor, evaluate, and optimize deployed models for performance, accuracy, and compliance with data security policies
- Present findings and insights in a clear and informative manner
- Apply NLP and text mining techniques for valuable insights
- Lead and mentor junior data science professionals
Requirements
- Over 6 years of professional experience in data science, machine learning engineering, or related fields on data-intensive projects
- Be up to date with research, find/test existing pretrained models, including multimodal models
- Be able to find datasets, generate synthetic datasets based on requirements
- Strong background in developing, validating, and deploying machine learning models for real-world applications
- Expertise in Python and popular data science libraries (e.g., scikit-learn, TensorFlow, PyTorch, pandas)
- Experience with cloud platforms (e.g., Microsoft Azure, AWS, GCP, OCI, IBM Cloud) for building and deploying AI solutions
- Ability to manage and document software requirements: elicit, break down, refine, estimate, prioritize, trace, change
- B2 level of English or higher, with an emphasis on technical communication skills
Nice to have
- Experience with deep learning, NLP, or computer vision projects
- Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes) for scalable model deployment
- Contributions to open-source AI/ML projects or publications in relevant fields
- Experience with superResolution, impainting, 3D impainting. Later integrate CV models with LLMs to explain the annotation in a human-readable format. Hands on with classic/linear algebra (affine 2D/3D/piece-wise transformations, optical flow, 2D/3D splines, fourier transformations, trigonometry).
- Solid understanding of data pipelines, ETL processes, and MLOps best practices
