Quantitative Research Intern: Signals & Backtesting (Remote)

Sryantra Capital; Singapore; On-site; SGD 20,000 - 38,000; Part time

Benefits offered by this job

Mentorship from senior researchers

Access to proprietary datasets

Competitive, performance-linked stipen

Flexible remote options

Job summary

Sryantra Capital invites students and early‑career researchers to join its quantitative research internship. You’ll work with senior researchers to move ideas from hypothesis to backtest and production, mining large-scale market data for predictive signals and inefficiencies.

You will be immersed in research, data cleaning, feature engineering, and deploying validated research with traders and developers across Singapore, New York, or remotely.

Qualifications

• Pursuing or recently completed degree in a quantitative field.
• Solid programming skills in Python.
• Strong grasp of probability, statistics, and time-series analysis.
• Fluency in English is required.

Responsibilities

• Research and backtest trading signals using statistical and machine-learning techniques.
• Clean, transform, and analyse large market datasets to surface predictive features.
• Investigate market microstructure and exchange dynamics with rigour and honesty.
• Contribute to portfolio construction and execution research aimed at better risk-adjusted returns.
• Document findings clearly and present them to traders and fellow researchers.
• Pair with developers and traders to deploy validated research into live systems.

Skills

Python

PyTorch

TensorFlow

scikit-learn

Probability & statistics

Time-series analysis

English fluency

Education

Quantitative degree (Math/Physics/Statistics/CS)

Tools

PyTorch

TensorFlow

scikit-learn

Job description

Sryantra Capital invites students and early‑career researchers to join its quantitative research internship. You’ll work with senior researchers to move ideas from hypothesis to backtest and production, mining large-scale market data for predictive signals and inefficiencies.

You will be immersed in research, data cleaning, feature engineering, and deploying validated research with traders and developers across Singapore, New York, or remotely.