2palpha

Quantitative Research Lead / Quant Trading Bot Developer US Stock Market Position : Full-time Location : Remote / WFH (US market overlap hours) Compensation : Competitive base salary + profit sharing from live strategies About Us Quant 2P Alpha is a quantitative trading and research startup focused on the US stock market . We are building our quant stack from the ground up from data research pipelines to execution systems. This role offers a unique opportunity to be the first quant hire and play a critical role in shaping our strategy, models, and infrastructure. Role Overview We are hiring a Quantitative Researcher / Quant Developer to: Build the research and execution framework from scratch. Design and backtest systematic trading models . Develop real-time trading bots using broker APIs (e.g., Interactive Brokers). Implement statistical, ML, and time-series models for signal generation. Optimize for latency, execution cost, and risk-adjusted returns . Ensure backtests replicate accurately in live trading . Bring an entrepreneurial mindset take ownership, solve problems independently, and thrive in a startup environment. Key Responsibilities Set up the quant research stack (data ingestion, feature engineering, model testing). Develop risk models, execution of stock trading algorithms (Algo), and monitoring systems . Maintain accurate logs, PnL tracking, and strategy metrics . Collaborate on new research in market inefficiencies and ML-based models . Required Skills Strong Python programming (NumPy, pandas, vectorized ops). Solid foundation in statistics, probability, and time-series analysis . Experience with backtesting frameworks and APIs (Interactive Brokers preferred). Knowledge of PnL, slippage, risk-reward, profit factor . Ability to write clean, production-ready code . Preferred Qualifications Degree in Math, Stats, CS, or Quantitative Finance (IIT, IISc, ISI, NIT, BITS, IIIT, CMI, DSE, Ashoka, or global equivalents). Experience in machine learning, data mining, or competitive programming . Participation in Kaggle, Codeforces, or similar competitions . Exposure to cloud platforms (AWS, GCP) and containerization (Docker, Kubernetes). Familiarity with stock markets or trading concepts (PnL, order execution, market data) is a plus but not required. What We Offer Competitive base salary . Profit-sharing (7 - 10%) on net profits from deployed strategies. Opportunity to build systems from scratch with full ownership of your models . Direct exposure to US markets and institutional-grade data. Flat structure, close mentorship, and fast-track growth . Selection Process Quantitative & Coding Assessment (Math, ML, Python, Time-Series). Technical interviews with founding team.