Job Description

Key Roles and Responsibilities of Position:

• • Partner with business stakeholders to understand challenges, define analytical approaches, and translate business requirements into data science solutions.
  • Analyze structured and unstructured datasets to identify trends, patterns, and actionable insights.
  • Design, build, validate, and deploy machine learning and statistical models to support business decision-making.
  • Develop Generative AI solutions leveraging prompt engineering, Retrieval-Augmented Generation (RAG), embeddings, and large language models.
  • Build and deploy autonomous and multi-agent systems using frameworks such as Google Agent Development Kit (ADK), LangGraph, LangChain, or similar orchestration platforms.
  • Design scalable data preparation, feature engineering, and data augmentation pipelines to improve model performance and robustness.
  • Support end-to-end model lifecycle activities, including problem scoping, experimentation, model training, evaluation, deployment, monitoring, and optimisation.
  • Ensure data quality, integrity, governance, and responsible AI practices throughout the analytics lifecycle.
  • Stay informed about emerging developments in machine learning, data science, Generative AI, and analytics methodologies, and apply relevant innovations to business challenges.
  • Communicate analytical findings and recommendations effectively to technical and non-technical audiences.

Minimum Qualifications

• • Bachelor's degree in Data Science, Computer Science, Statistics, Applied Mathematics, Operations Research, Engineering, or a related quantitative discipline.
  • 4+ years of hands-on experience applying machine learning techniques including regression, classification, clustering, decision trees, random forests, and support vector machines.
  • 4+ years of experience using Python for data analysis, machine learning, and visualisation, including libraries such as Pandas, NumPy, Matplotlib, and Seaborn.
  • 4+ years of experience in SQL and relational database systems.
  • 2+ years of experience developing Generative AI applications using prompt engineering, RAG architectures, embeddings, or model fine-tuning techniques.
  • Experience developing AI agents or agentic workflows using Google ADK, LangGraph, LangChain, or similar frameworks.
  • Familiarity with vector databases and semantic retrieval platforms such as FAISS, Pinecone, Vertex AI Vector Search, or similar technologies.

Preferred Qualifications

• • Master's degree or PhD in Computer Science, Statistics, Applied Mathematics, Operations Research, Engineering, or a related quantitative field.
  • Experience developing and deploying machine learning solutions on Google Cloud Platform (GCP).
  • Strong understanding of probability, statistical inference, linear algebra, numerical methods, optimisation, and neural network fundamentals.
  • Excellent problem-solving, communication, stakeholder management, and presentation skills.
    
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