Lead Data Scientist
Strong programming skills in Python (including best practices for clean, maintainable code); familiarity with web frameworks (e.g., Flask, FastAPI, or Django).
Proficiency in containerisation and orchestration tools.
Familiarity with LLM fine-tuning, prompt engineering, agentic frameworks and solution deployment using modern frameworks (e.g., LangGraph, LangChain).
Expertise in data processing and transformation using Pandas, NumPy, and SQL (ideally PySpark).
Ability to translate business problems into scalable, production-grade solutions.
Excellent communication and collaboration skills, with the ability to work effectively in an off-shore setting and maintain strong relationships with UK-based teams.
Ability to work in a fast-paced environment and manage multiple projects simultaneously.
Knowledge & Experience
Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field.
3+ years of experience in software engineering, data science, machine learning, or AI engineering.
Hands-on experience in developing and deploying GenAI/LLM applications in production environments, including containerisation and CI/CD pipelines.
Exposure to cloud platforms (ideally Azure and Databricks).
Bonus: Experience working with large-scale datasets and distributed computing (Spark or similar).
Develop and deploy machine learning models for analytics and automation
Analyze data to support business strategy and decision-making
Design solutions to improve financial service operations
Collaborate with engineering and business teams
Maintain data pipelines and support real-time analytics
Use machine learning to enhance risk assessment and fraud detection
Communicate insights through reports and dashboards
Stay current with trends in data science and financial technology
Proficient in Python, R, or Scala
Experienced in data cleaning using Pandas, NumPy, and SQL
Skilled with machine learning tools like TensorFlow, PyTorch, and Scikit-learn
Strong problem-solving and analytical thinking
Able to explain complex data to non-technical stakeholders
Capable of managing multiple projects in a fast-paced environment
Degree in Computer Science, Data Science, Statistics, or a related field
Over three years of experience in data science or machine learning
Experienced with large datasets and distributed computing like Spark or Hadoop
Strong understanding of statistics, probability, and optimization
Familiar with cloud platforms such as AWS, GCP, or Azure
Background in financial services including trading or risk management is a plus