About The Company
We are representing a research and technology organization focused on developing advanced analytical solutions that combine data science, machine learning, and artificial intelligence.
About The Company
We are representing a research and technology organization focused on developing advanced analytical solutions that combine data science, machine learning, and artificial intelligence.
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.
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