Quant/Data Scientist: ML Trading & Deployment Expert

Prediction Machine LLC; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Prediction Machine LLC in San Francisco is seeking a quants or data scientist to build and deploy scalable machine learning algorithms for trading. You will work with a motivated team on developing trading strategies and monitoring the health of deployed models.

Ideal candidates have 3+ years in Python, SQL and ML, experience with GPUs, and strong data processing skills with pandas, numpy, scipy, and pyAthena. Collaboration with domain experts is essential.

Qualifications

• 3+ years of experience in Python, SQL, machine learning.
• Experience with GPUs for ML training/inference is a plus.
• 3+ years in data processing libraries (pandas, numpy, scipy, pyAthena).
• 3+ years in REST APIs, Flask, FastAPI.
• 2+ years of experience on AWS or another cloud platform.
• Experience with large-scale time series/finance/quants datasets.
• Strong deployment-grade ML experience.
• Proven ability to write clean, engineered ML code.
• Experience collaborating across disciplines with domain experts.
• Knowledge of AWS Athena and Redshift is a plus.
• Exposure to distributed computing (PySpark or similar) is a plus.
• Strong oral and written communication skills.

Responsibilities

• Build and deploy scalable machine learning algorithms for trading.
• Monitor the health of deployed algorithms and data pipelines.
• Rigorous testing for data integrity, statistical significance, and numerical stability.

Skills

Python

SQL

Machine Learning

Pandas

NumPy

SciPy

pyAthena

REST APIs

Flask

FastAPI

AWS

Time Series Data

Deployment of ML

Engineering Fundamentals

Communication Skills

Independent Working

Tools

AWS

AWS Athena

Redshift

PySpark

Job description

Prediction Machine LLC in San Francisco is seeking a quants or data scientist to build and deploy scalable machine learning algorithms for trading. You will work with a motivated team on developing trading strategies and monitoring the health of deployed models.

Ideal candidates have 3+ years in Python, SQL and ML, experience with GPUs, and strong data processing skills with pandas, numpy, scipy, and pyAthena. Collaboration with domain experts is essential.