Sapiens Alpha

Quant Researcher & Developer - BSFI

Job Description:

We are seeking an exceptionally talented Quantitative Developer to join our core research and development team. You will be instrumental in the entire lifecycle of our investment models-from initial idea generation and data analysis to the implementation and optimization of production-level systems. This is not a trading role; it is a deep, research-oriented position focused on creating and refining long-term, systematic investment strategies using cutting-edge statistical, machine learning and reinforcement learning techniques.

Key Responsibilities:

- Research, design, and implement quantitative models for systematic portfolio construction and asset allocation.

- Machine Learning and statistics applications: Apply statistical optimization techniques, advanced ML, Deep learning, and reinforcement learning to financial dataset to optimize portfolios for alpha generation.

- Data Engineering: Build and maintain robust data pipelines for sourcing, cleaning, and processing structured and unstructured financial data.

- Systematic Implementation: Translate research models into clean, efficient, and robust production-grade code primarily in Python.

- Rigorous back-testing: Develop and manage a rigorous back testing framework to validate model performance, ensuring statistical significance and robustness of alpha generation and portfolio parameters against various market conditions.

- Portfolio Risk Analysis: Continuously monitor and analyze model performance and portfolio risk, contributing to the ongoing refinement of our investment framework.

Preferred Qualifications:

- Educational Background: An advanced degree (Masters or PhD) from a top-tier institution in a quantitative field such as Computer Science, Statistics, Economics, or Mathematics.

- Programming Expertise: Expert-level proficiency in Python and its scientific computing stack (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow).

- Quantitative Skills: Deep understanding of probability, statistics, optimization, and time-series analysis.

- Experience: Demonstrable experience applying machine learning and/or reinforcement learning and deploying them at investment firms

- Problem-Solving Mindset: A strong foundation in logical reasoning, an ability to think independently and critically, and an intense intellectual curiosity.

What We Offer

- Industry compensation A highly competitive compensation package, including a significant performance-based bonus structure.

- The opportunity to work on intellectually stimulating problems at the intersection of AI and finance.

- Direct impact on the firm's core investment strategies and success from day one.

- A flat, collaborative, and meritocratic culture free from bureaucracy.