About The Position

Meriton is seeking a highly motivated IT & Data Analytics Intern with a strong interest in Artificial Intelligence, Machine Learning, and Data Science. This role is ideal for students who enjoy problem‑solving, exploring emerging technologies, and applying analytics to drive insights and operational excellence. You’ll work closely with the Meriton technology team to support internal analytics, automation projects, and AI‑driven initiatives that enhance business decision‑making and improve efficiency.

Requirements

  • Currently pursuing a degree in Computer Science, Data Science, Information Systems, Statistics, Engineering, or related fields.
  • Foundational coursework or hands‑on experience in: Artificial Intelligence / Machine Learning Data Science methodologies Python, R, SQL, or similar languages
  • Comfortable working with modern AI coding tools such as: Cursor (AI coding environment) Claude Code / Claude AI AI Foundry or other LLM ops platforms
  • Strong analytical thinking, problem‑solving abilities, and attention to detail.
  • Eagerness to learn, experiment, and adopt emerging technologies.

Nice To Haves

  • Experience with: Jupyter Notebooks Pandas, NumPy, Scikit‑Learn, PyTorch or TensorFlow Git / version control Power BI or Tableau
  • Familiarity with API calls, cloud platforms, or DevOps automation.
  • Prior hands‑on project work involving AI agents, ML modeling, or generative AI use cases.

Responsibilities

  • Assist in building and evaluating machine learning models, including data preprocessing, feature engineering, and model validation.
  • Use tools such as Cursor, Claude Code, AI Foundry, and similar AI development platforms to prototype automation and analytics solutions.
  • Conduct exploratory data analysis (EDA) on structured and unstructured datasets.
  • Support the creation of dashboards, reports, and visualizations for business stakeholders.
  • Research and recommend AI use cases that align with team strategy and business needs.
  • Collaborate with IT partners to streamline workflows through scripts, automation, and analytics.
  • Troubleshoot data, system, or integration issues as needed.
  • Document technical processes, workflows, and best practices.
  • Experiment with generative AI tools to assist with: Query generation Code generation & refactoring Data pipeline development Business insights summarization Workflow automation
  • Partner with team members to test, evaluate, and implement AI‑powered solutions.
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