Lead Data Scientist

• Develop and maintain scalable applications using Python following best practices for clean efficient and maintainable code.
• Build APIs and backend services using modern frameworks such as Flask FastAPI or Django.
• Work with containerization and orchestration technologies to support deployment and scalability of applications.
• Design develop and deploy GenAI and LLM-based solutions using frameworks such as LangChain and LangGraph.
• Apply prompt engineering techniques and support LLM fine-tuning to optimize model performance.
• Build and optimize data pipelines and perform data processing and transformation using tools like Pandas NumPy SQL and ideally PySpark.
• Translate business requirements into scalable production-ready technical solutions.
• Collaborate with cross-functional and offshore teams including UK-based stakeholders ensuring clear communication and alignment.
• Manage multiple projects in a fast-paced environment while maintaining delivery quality and timelines.

Requirements

• Bachelors or Masters degree in Computer Science Data Science Statistics or a related discipline.
• Minimum 3 years of experience in software engineering data science machine learning or AI engineering roles.
• Strong proficiency in Python with hands-on experience in backend development and API frameworks.
• Experience in deploying GenAI/LLM applications in production environments.
• Solid understanding of containerization CI/CD pipelines and modern deployment practices.
• Experience working with cloud platforms preferably Azure along with Databricks exposure.
• Strong skills in data manipulation and analysis using Pandas NumPy SQL and PySpark (preferred).
• Familiarity with distributed data processing frameworks such as Spark is an added advantage.
• Excellent communication and collaboration skills especially in distributed/offshore team environments.