Researcher (Data Science & AI)

Overview
We are looking for an AI Researcher to join the R&D team to work on applied AI, statistical modelling, predictive systems, and LLM-powered agent development. This role focuses on building intelligent analytical systems that combine machine learning, structured data processing, and AI agents to solve real-world research and business problems.

Responsibilities

• Conduct exploratory data analysis (EDA), statistical modelling, and predictive analytics using structured and unstructured datasets.
• Design, develop, and evaluate machine learning models including regression, classification, and forecasting models.
• Build and develop AI agents powered by LLMs to automate research workflows and analytical tasks.
• Integrate AI agents with databases, predictive models, and data pipelines for end-to-end reasoning and orchestration.
• Evaluate AI agent performance including reasoning quality, tool usage accuracy, hallucination handling, and task completion.
• Develop clean, scalable, and well-documented Python code for data processing, feature engineering, modelling, and visualisation.
• Query and manipulate structured datasets using SQL.
• Contribute to shared codebases, experiment tracking, and reproducible AI/data science workflows.
• Present technical findings and research insights clearly to both technical and non-technical stakeholders.
• Participate in research reviews, peer code reviews, and collaborative knowledge-sharing sessions.

Requirements

• Bachelor’s, Master’s, or PhD in Computer Science, Mathematics, Statistics, Engineering, Data Science, or related quantitative disciplines.
• Strong foundation in Python programming and data science libraries such as Pandas, NumPy, Scikit-learn, SciPy, and Matplotlib.
• Knowledge of statistical modelling, machine learning, and mathematical concepts including linear algebra, calculus, and optimisation.
• Hands-on experience with data wrangling, feature engineering, handling missing data, and structured datasets.
• Familiarity with supervised, unsupervised, and generative AI models.
• Exposure to LLMs, AI agents, or agentic AI frameworks is advantageous.
• Experience with SQL and relational databases..
• Fresh graduates with internships, research projects, Kaggle competitions, or open-source contributions are welcome to apply