Skip to content

Aryan Dutt / SINGAPORE

Available for research and engineering opportunities

Data Science & AI @ NTU

Aryan Dutt

Data Science & AI undergraduate at NTU Singapore, working across distributed infrastructure, scientific machine learning, probabilistic risk modelling, and quantitative systems.

Work locations

13 roles across three cities.

  • Singapore: TikTok (Incoming), Akro (Hybrid), SMART (Hybrid), NTU SC3DP (On-site), InterSystems (On-site), NTU SC3DP (Hybrid), SEAQR (Remote), Tagit (On-site), BioMetallica (On-site), Ministry of Home Affairs (On-site), Stealth Startup (Remote)
  • Cambridge, MA: MIT Julia Lab (Remote)
  • London: General Learning (YC F24) (Remote)
On-site and hybridRemote

Profile at a glance

Focus
Systems / ML / Quant
Base
Singapore
Languages
Python, C++, Julia, TypeScript
Current interests
Market microstructure, evaluation harness design, and systems where tail latency is the metric that matters
Status
Building and researching, open to 2027 roles and collaborations

01/Selected work

All projects

02/Experience

Full timeline
  1. Engineering

    TikTok

    Incoming Software Engineer Intern

    Joining the Global Live Transaction team as a Software Engineer Intern, on the distributed payment infrastructure that team owns.

    Jan – May 2027

  2. Engineering

    Akro

    Member of Technical Staff

    Building probabilistic risk models for critical infrastructure, where the useful output is a calibrated distribution rather than a single number.

    Oct 2026 – Present

  3. Research

    Singapore-MIT Alliance for Research and Technology

    Visiting Student

    Selected for a visiting research appointment at SMART, under Prof. Rajeev J. Ram of MIT EECS and the Research Laboratory of Electronics.

    Oct 2026 – Present

  4. Engineering

    InterSystems

    Software Engineer Intern

    Built an Ansible-based automation framework for InterSystems IRIS that provisions databases, namespaces, web applications, and security settings across environments.

    May – Jul 2026

  5. Research

    MIT Julia Lab

    Research Intern

    Worked on NeuralLyapunov.jl in the MIT Julia Lab under Dr. Chris Rackauckas, in the part of scientific machine learning where numerical solvers and learned models have to agree with each other.

    Jul 2025 – Mar 2026

  6. Engineering

    Tagit

    Software Engineer

    Architected a modular transaction anomaly detection system for digital banking, modelling outliers with per-user Isolation Forests and shipping the dashboard that let analysts act on what it flagged.

    Jan – Mar 2025

03/Research notes

All writing

Featured

17 October 2026 · 4 min

Why I keep ending up between solvers and models

Scientific machine learning, probabilistic risk, and real-time data platforms look like three unrelated fields. Working across them, they rhyme more than they differ.

04/Contact

Building something difficult?