We are looking for an experienced Senior Data Scientist with strong expertise in Python, Machine Learning, Generative AI, Large Language Models (LLMs), and AI engineering to develop intelligent, scalable, and data-driven solutions. The ideal candidate will combine statistical expertise and analytical thinking with practical experience building AI applications, retrieval-augmented generation (RAG) pipelines, AI agents, and production-ready machine learning systems.
You will work on complex business challenges, translating data and analytical requirements into innovative solutions that improve decision-making, automate workflows, and deliver measurable business value.
Requirements
Key Responsibilities
Translate business challenges into analytical problems and deliver actionable, data-driven recommendations.
Collect, process, cleanse, and validate data to ensure accuracy, consistency, and analytical reliability.
Develop and optimise machine learning models, classifiers, predictive systems, and automation solutions.
Build AI-powered applications, including chatbots, RAG pipelines, workflow agents, and multi-agent systems .
Develop Python-based APIs and microservices integrating LLMs from OpenAI, Anthropic, AWS, Azure, and Google Cloud.
Design retrieval, embedding, inference, and knowledge-processing pipelines using vector databases and knowledge graphs.
Implement AI and machine learning workloads on AWS, Azure, and GCP using scalable cloud architectures.
Establish deployment, evaluation, monitoring, and retraining pipelines for production AI systems.
Apply infrastructure-as-code practices using tools such as Terraform and CloudFormation.
Develop automated anomaly detection systems, dashboards, and reporting solutions for continuous monitoring.
Conduct statistical analysis, hypothesis testing, experimentation, and exploratory data analysis.
Present findings, model outcomes, and recommendations clearly to clients and business stakeholders.
Ensure AI solutions follow appropriate security, governance, reliability, and responsible AI practices.
Participate in architecture discussions and code reviews while maintaining clean, maintainable code.
Manage project delivery, mentor junior team members, and contribute to recruitment and knowledge-sharing initiatives.
What Makes You a Great Fit
5+ years of experience in data science, analytics, machine learning, or applied AI.
Strong programming skills in Python , with hands-on experience developing production-grade data and AI applications.
Expertise in machine learning algorithms, including regression, classification, optimisation, and neural networks.
Strong understanding of statistical analysis, probability distributions, hypothesis testing, and experimental design.
Practical experience with Generative AI, LLMs, RAG, LangChain, LangGraph, or AutoGen .
Knowledge of vector databases, embeddings, retrieval systems, knowledge graphs, and AI agent architectures.
Experience with cloud AI/ML services such as AWS Bedrock and SageMaker, Azure OpenAI and AI Studio, or GCP Vertex AI and Gemini .
Familiarity with MLOps/LLMOps, CI/CD, Docker, Kubernetes, and event-driven systems.
Experience with relational databases, SQL, and NoSQL or big-data technologies such as MongoDB, Cassandra, or Hadoop.
Proficiency in data visualisation tools such as Tableau, Power BI, QlikView, or D3.js.
Strong analytical, problem-solving, communication, and stakeholder-management skills.
Ability to manage projects end to end, collaborate across teams, and mentor emerging talent.
A bachelor's degree in Engineering, Computer Science, or a related analytical discipline is preferred; a relevant master's degree is an advantage.
A continuous-learning mindset and strong interest in Generative AI, AI safety, intelligent automation, and emerging technologies .
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