Junior Data Scientist（AI modeling）

Job Summary

We are looking for a motivated Junior Data Scientist – AI Modeling to join our data and AI team. This role will support the development, evaluation, and deployment of machine learning and AI models using structured and unstructured data.

The ideal candidate has a solid foundation in Python, statistics, machine learning, and data analysis, with hands-on experience through academic projects, internships, research, or personal projects. This is a great opportunity for candidates looking to build practical experience in Data Science, Machine Learning, and Applied AI.

Responsibilities

Collect, clean, preprocess, and analyze structured and unstructured datasets.

Perform exploratory data analysis (EDA) and identify meaningful patterns and trends.

Develop and evaluate machine learning models for classification, regression, clustering, forecasting, and other business use cases.

Assist with feature engineering, feature selection, and model optimization.

Train and evaluate AI/ML models using Python-based machine learning frameworks.

Compare model performance using appropriate evaluation metrics.

Support the development of predictive modeling and AI-driven solutions.

Participate in experiments involving traditional machine learning and modern AI/LLM technologies.

Work with data stored in SQL databases and other data sources.

Create reusable Python scripts and data pipelines for model development.

Document modeling methodology, assumptions, experiments, and results.

Collaborate with Data Scientists, Machine Learning Engineers, Data Engineers, and business teams.

Assist with model deployment, testing, monitoring, and performance improvement.

Stay current with developments in machine learning, generative AI, and data science.
Required Qualifications

• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Economics, or a related quantitative field.
• Strong programming skills in Python.
• Understanding of statistics, probability, and fundamental machine learning concepts.
• Experience with Python libraries such as:
  • Pandas
  • NumPy
  • Scikit-learn
  • Matplotlib
• Understanding of supervised and unsupervised machine learning techniques.
• Familiarity with model evaluation metrics and validation techniques.
• Basic SQL skills for querying and manipulating data.
• Ability to analyze datasets and communicate findings clearly.
• Strong analytical, problem-solving, and learning abilities.

Preferred Qualifications

• Experience with PyTorch or TensorFlow.
• Exposure to Natural Language Processing (NLP), deep learning, or computer vision.
• Familiarity with Large Language Models (LLMs) and Generative AI.
• Basic understanding of prompt engineering, embeddings, vector databases, or RAG.
• Experience with APIs, FastAPI, or Flask.
• Familiarity with Git and version control.
• Exposure to cloud platforms such as AWS, Azure, or Google Cloud.
• Experience with visualization tools such as Tableau or Power BI.
• Internship, research, coursework, or project experience involving machine learning or AI modeling.

Example Technical Skills

Programming: Python, SQL
Data Analysis: Pandas, NumPy, SciPy
Machine Learning: Scikit-learn, XGBoost, LightGBM
Deep Learning: PyTorch, TensorFlow
AI / NLP: Transformers, Hugging Face, LLMs, Embeddings, RAG
Visualization: Matplotlib, Tableau, Power BI
Development: Git, REST APIs, FastAPI
Cloud: AWS, Azure, GCP

What You Will Learn

In this position, you will gain hands-on experience in:

• End-to-end machine learning development
• AI model training and evaluation
• Data preprocessing and feature engineering
• Predictive modeling
• Applied Generative AI and LLM technologies
• Model deployment and production AI workflows
• Working with real-world business and technical datasets

We welcome candidates with strong fundamentals and relevant academic, internship, research, or project experience who are interested in developing their careers in Data Science, Machine Learning, and Artificial Intelligence.