Data Scientist

Job Title: Senior Data Scientist Experience: 6+ Years Location: Hybrid (Remote) Qualification: Bachelor's or Master's Degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Statistics, Mathematics, Engineering, or related field About Cloudaeon Cloudaeon is a global technology consulting and services company. We support companies in managing cloud infrastructure and solutions with the help of big data, DevOps, analytics, and Artificial Intelligence. We offer first-class solutions and services that leverage modern AI technologies to help enterprises transform business processes and customer experiences. Our deep industry expertise combined with strong technology capabilities enables us to deliver innovative and impactful solutions for global customers. Our global team consists of experienced professionals across data, AI, cloud, and digital transformation domains, committed to helping customers achieve their business goals. Role Overview We are looking for an experienced and innovative Senior Data Scientist to join our AI and Data Science practice. The ideal candidate will have strong expertise in Machine Learning, Recommendation Systems, Personalisation, and Generative AI to build intelligent customer experiences. This role involves designing and deploying scalable AI solutions that deliver highly personalised product recommendations, conversational AI experiences, and advanced predictive capabilities. The successful candidate will work closely with Data Engineers, MLOps Engineers, Product Managers, Business Stakeholders, and Engineering teams to transform business problems into production-ready AI solutions that create measurable customer and commercial value. Key Responsibilities Design, develop, and deploy Machine Learning models for recommendation systems, personalisation, and customer intelligence. Build AI-powered recommendation engines using retrieval, ranking, and advanced personalisation techniques. Develop and optimise conversational AI and Generative AI solutions powered by Large Language Models (LLMs). Design scalable end-to-end ML pipelines from data preparation through model deployment and monitoring. Perform exploratory data analysis, feature engineering, model experimentation, validation, and continuous optimisation. Develop evaluation frameworks to measure model quality, recommendation relevance, user satisfaction, and business impact. Collaborate with Product Managers, Engineering teams, MLOps, and business stakeholders to deliver AI solutions aligned with customer and commercial objectives. Drive continuous experimentation using A/B testing, statistical analysis, and performance monitoring. Ensure AI solutions meet performance, scalability, reliability, and production readiness standards. Mentor junior data scientists and promote best practices in machine learning, software engineering, and AI development. Communicate technical findings and business insights effectively to both technical and non-technical stakeholders. Required Skills 6+ years of experience in Data Science, Machine Learning, Artificial Intelligence, or Advanced Analytics. Strong programming experience in Python and the data science ecosystem including Pandas, NumPy, and Scikit-learn. Strong understanding of Machine Learning algorithms, statistical modelling, feature engineering, and experimental design. Experience building and deploying end-to-end Machine Learning solutions in production environments. Strong understanding of recommendation systems, personalisation techniques, retrieval and ranking architectures. Experience with Large Language Models (LLMs), Generative AI, and conversational AI applications. Experience working with distributed data processing frameworks such as Apache Spark or PySpark is desirable. Solid understanding of software engineering best practices including version control, modular programming, testing, and CI/CD. Strong analytical, problem-solving, and critical thinking skills. Excellent verbal and written communication skills. Strong stakeholder management and ability to explain complex AI concepts to business users. Ability to work collaboratively across cross-functional teams in agile environments. Good to Have Experience in Retail, E-commerce, Customer Analytics, or Personalisation domains. Hands-on experience with recommendation engines, vector databases, embeddings, and similarity search techniques. Experience with cloud platforms such as Microsoft Azure, AWS, or Google Cloud. Knowledge of MLOps practices, model deployment, monitoring, and automation. Experience with LLM orchestration frameworks such as LangChain, Semantic Kernel, or similar technologies. Familiarity with Databricks, Azure Machine Learning, MLflow, or equivalent ML platforms. Exposure to experimentation platforms and A/B testing frameworks. Experience mentoring technical teams and leading AI initiatives. Knowledge of Responsible AI, model governance, explainability, and AI ethics.