Salary: 45,000 - 70,000 GBP per year Requirements:
* PhD or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
* A minimum of 5 years of industry experience as a Data Scientist, with a specialization in ML Modelling, Ranking, Recommendations, or Personalization systems.
* Proven experience in designing and developing scalable machine learning systems for training, inference, monitoring, and iteration.
* Strong understanding of ML/DL/LLM algorithms, model architectures, and training methodologies.
* Proficient in Python, SQL, Spark, PySpark, TensorFlow, or other analytical/model-building programming languages.
* Familiarity with tools and Large Language Models (LLMs).
* Ability to work both independently and collaboratively within a team.
Responsibilities:
* As a Data Science Developer, I will:
* Develop and coordinate plans for analytical initiatives, ensuring alignment with business objectives.
* Manage deliverables in an agile setting, maintaining clear communication with all stakeholders.
* Present analytical findings, status updates, and potential issues to various audience groups, including business, technology management, and model governance.
* Conduct data modeling and cleaning from both internal and external sources to ensure data integrity.
* Build predictive and prescriptive models, utilizing advanced techniques to manipulate and clean data results.
* Develop, manage, and deploy analytical solutions using Machine Learning (ML), Deep Learning (DL), and Large Language Models (LLMs), ensuring production systems adhere to technology SDLC processes.
* Implement features through the full ML lifecycle, including Development, Testing, Training, and Monitoring/Evaluation to guarantee scalability and reliability.
Technologies:
* AI
* Hadoop
* Hive
* LLM
* Machine Learning
* MySQL
* Python
* PySpark
* SQL
* Spark
* TensorFlow
* Support
More:
Preferred skills include experience in Generative AI (GenAI) and LLM projects, familiarity with distributed data/computing tools (e.g., Hadoop, Hive, Spark, MySQL), a background in the financial industry, particularly in banking and risk management, and knowledge of capital markets, financial instruments, and modeling techniques.
I invite you to join us in shaping the future of data science in finance! We are committed to an inclusive and accessible recruitment process, supporting candidates of all backgrounds and abilities. If you require reasonable adjustments at any stage, please let us know, and we will be happy to assist you.