Job Openings
Sr Data Scientist
About the job Sr Data Scientist
Main Goals and Responsibilities:
- Lead the development and deployment of robust data science and machine learning pipelines, from data retrieval and preprocessing to model training, inferencing, and results visualisation;
- Take ownership of the architecture and optimisation of DS/ML pipelines to ensure scalability and efficiency;
- Leverage ML models to build innovative solutions for tasks such as text generation, content automation, and more;
- Collaborate with cross-functional teams to integrate advanced data solutions that meet evolving business needs;
- Guide tools, strategies, and best practices to solve complex data science problems, including those involving LLMs and Generative AI;
- Share expertise with the team and across departments to elevate the overall technical capabilities of the organisation;
- Proactively identify opportunities to improve data processes, model performance, and business impact.
Required Skills and Experience:
- English level Upper Intermediate +
- 5 - 8 years of Experience
- Strong mathematical and statistical background, including tensor calculus
- Expertise in databases such as Postgres, MongoDB, and SQL
- Proficiency in Python, with extensive experience in libraries such as Scikit-learn, Numpy, Pandas, and Matplotlib
- In-depth knowledge and experience with gradient boosting algorithms (e.g., XGBoost, LightGBM)
- Advanced experience with at least one neural network framework (TensorFlow/Keras, PyTorch), with a deep understanding of neural network architectures and optimisation techniques
- Proven commercial experience with classic machine learning and deep learning, including NLP and computer vision (e.g., BERT, ResNet)
- Experience in applying LLMs and Generative AI technologies (e.g., GPT, transformer-based architectures) in real-world use cases
- Extensive experience in building end-to-end machine learning pipelines (data ingestion, preprocessing, model training, deployment, inference) and managing CI/CD workflows using GitHub/GitLab
- Practical experience with Docker or Kubernetes platforms for deployment and scalability
- Commercial experience with cloud platforms like AWS or Azure
Nice to Have:
- Familiarity with big data tools such as Spark and Airflow