🛠 Tech Stack

💼 About This Role

You'll develop and deploy machine learning models for financial forecasting and pattern recognition using large-scale datasets. Your work will directly impact predictive accuracy and signal quality for a fast-growing financial intelligence firm. You'll collaborate with cross-functional teams to translate complex findings into actionable insights.

🎯 What You'll Do

• Develop and deploy ML models for forecasting and pattern recognition.
• Design and maintain scalable data preparation and feature engineering workflows.
• Conduct backtesting, validation, and performance analysis of models.
• Identify proprietary indicators and predictive features from alternative data.

📋 Requirements

• Bachelor's/Master's in quantitative field (Statistics, Math, CS, Physics, etc.)
• 2+ years experience with large-scale analytical or financial datasets
• Advanced Python including Pandas, NumPy, Scikit-Learn, PyTorch, TensorFlow
• Strong SQL and data querying capabilities

✨ Nice to Have

• Familiarity with financial markets and trading concepts
• Experience with high-volume or real-time datasets

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3Hiring Manager Interview· 45 min