Applied AI Researcher (LLMs, Agents & Machine Learning)

JAC RECRUITMENT PTE. LTD.; Singapore; On-site; SGD 90,000 - 140,000; Full time

Job summary

JAC RECRUITMENT PTE. LTD. represents a research and technology organization in Singapore focused on advanced analytics using data science, ML, and AI. The role involves analyzing data, building predictive models, performing EDA, and developing AI agents to automate workflows.

You will work with Python, SQL, and visualization tools, validate models, run experiments, and present insights to stakeholders. Fresh graduates with strong technical foundations are encouraged to apply.

Qualifications

• Bachelor's degree or higher in a quantitative field.
• Familiarity with Python data science stack and libraries.
• Experience with data wrangling, feature engineering, and statistical methods.

Responsibilities

• Analyze structured and unstructured data to identify patterns and insights.
• Develop predictive models including regression, classification, and time-series forecasting.
• Conduct EDA, feature engineering, data quality assessment, and model validation.
• Design and execute statistical experiments, including hypothesis testing and power analysis.
• Research and develop AI agents powered by LLMs to automate workflows.
• Integrate AI agents with databases, models, and data pipelines for autonomous querying and interpretation.
• Evaluate agent performance across tasks, reasoning, tool use, and failures.
• Build scalable data processing, ML, and visualization solutions using Python.
• Query, manipulate, and analyze data from relational databases using SQL.
• Contribute to reproducible pipelines, experiment tracking, code reviews, and documentation.
• Present findings to technical and non-technical stakeholders.

Skills

Python

Pandas

NumPy

Scikit-learn

SciPy

Matplotlib

Seaborn

Feature engineering

Data wrangling

EDA

Hypothesis testing

Education

Bachelor's degree in Computer Science or related field

Master's degree in Data Science or related field

PhD in a quantitative discipline

Tools

SQL

Job description

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