Applied AI Researcher (LLMs, Agents & Machine Learning)

COMPANY OVERVIEW We are representing a research and technology organization focused on developing advanced analytical solutions that combine data science, machine learning, and artificial intelligence. JOB RESPONSIBILITIES ·        Analyze structured and unstructured data to identify patterns, trends, and statistically significant insights that support research and business objectives. ·        Develop and apply predictive models, including regression, classification, time-series forecasting, and other statistical or mathematical modeling techniques. ·        Conduct exploratory data analysis (EDA), feature engineering, data quality assessment, and model validation using appropriate evaluation frameworks. ·        Design and execute statistical experiments, including hypothesis testing, significance testing, and power analysis. ·        Research, design, and develop AI agents powered by Large Language Models (LLMs) to automate and orchestrate analytical workflows. ·        Integrate AI agents with databases, predictive models, and data pipelines to enable autonomous querying, reasoning, and interpretation of results. ·        Evaluate agent performance across task completion, reasoning quality, tool utilization, hallucination rates, and failure handling. ·        Build scalable data processing, machine learning, and visualization solutions using Python and related technologies. ·        Query, manipulate, and analyze data from relational databases using SQL. ·        Contribute to reproducible data pipelines, experiment tracking, code reviews, technical documentation, and research reporting. ·        Present technical findings and recommendations to both technical and non-technical stakeholders. JOB REQUIREMENTS ·        Bachelor's, Master's, or PhD in Computer Science, Data Science, Mathematics, Statistics, Physics, Engineering, or a related quantitative discipline. Fresh graduates with strong technical foundations are encouraged to apply. ·        Proficiency in Python and core data science libraries, including Pandas, NumPy, Scikit-learn, SciPy, Matplotlib, and Seaborn. ·        Strong understanding of data wrangling, feature engineering, data normalization, missing data handling, and outlier detection. ·        Solid mathematical foundations in linear algebra, calculus, optimization, probability. Working Location: Singapore Syahirah Binte Ahmad Ja'afar (R22105331) JAC Recruitment Pte. Ltd. (90C3026)