AI ML Quantitative Researcher - Alpha Discovery ( Hybrid )

Position Summary Nurp is seeking a senior AI/ML quantitative researcher to deepen and scale our alpha discovery and portfolio decision‑making capabilities. This role focuses on applying advanced machine learning to existing quantitative strategies, signals, and live portfolios rather than purely theoretical research. You will work directly with production strategies, proprietary data, and live trading systems to determine which signals are selected, how risk is managed in real time, and how existing strategies can be enhanced through ML‑driven intelligence. This role will work out of our Miami office three days per week and remotely for the remaining two days. Competitive annual salary ranging from $200,000 to $400,000 plus a meaningful revenue‑share component. About the Company Nurp builds smart trading algorithms that help people trade more effectively across multiple markets, including forex, gold, and more. We’re reshaping the way people invest by using powerful, data‑driven technology instead of outdated methods. At Nurp, we’re focused on growth, both in the markets we serve and in the people we hire. This is a place for driven, results‑oriented individuals who want to take ownership, learn quickly, and make an impact. You’ll work alongside a talented team, contribute to meaningful projects, and help shape the future of algorithmic trading. We move fast and wear many hats, creating constant opportunities for personal and professional growth. Key Responsibilities Develop machine learning models that evaluate and select financial signals across multiple quantitative strategies, determining which trades to execute based on market conditions, diversification impact, and correlation behavior. Design ML‑driven frameworks to combine and weight signals dynamically, improving portfolio‑level performance and robustness. Build automated ML‑based monitoring systems for live strategies to assess expected performance, identify underperforming trades, and support real‑time risk management. Apply machine learning techniques to dynamically manage exposure, directional bias, and risk as market conditions evolve. Enhance existing quantitative strategies using ML, including improvements to entry and exit timing, position sizing, and market regime detection. Own feature engineering and data experimentation using market data, strategy outputs, and portfolio‑level signals to improve model performance. Collaborate closely with quantitative strategists and developers to ensure models are production‑ready and integrated into live trading systems. Define data requirements and maintain reliable research and production pipelines that support ongoing ML‑driven strategy improvement. Perform other related duties as necessary or assigned. Key Competencies Proven Alpha Generation – A demonstrated, institutional track record of developing or conceiving trading algorithms or signals with measurable portfolio impact. Expert Level Machine Learning – Deep expertise in machine learning techniques, statistical modeling, and predictive analytics applied to financial markets. Technical Proficiency – Strong proficiency in Python and core data science libraries including Pandas, NumPy, Scikit‑learn, TensorFlow, or PyTorch. Portfolio and Risk Mindset – Ability to think at the portfolio level, balancing alpha generation, correlation, and risk management. Collaborative Execution – Strong communication and collaboration skills to work effectively with quantitative researchers, engineers, and product teams. Financial Market Acumen – Deep understanding of market structure, trading strategies, and what constitutes deployable alpha. Education and Experience Master’s or Ph.D. in quantitative finance, financial engineering, computer science, or a related field. At least 5 years of proven experience applying machine learning techniques and trading algorithms to financial markets. At least 7 years of experience working within a financial institution, hedge fund, prop desk, or fintech company. Proficiency in Python, R, or MATLAB and familiarity with machine learning frameworks. In-depth understanding of financial markets, trading strategies, and risk management principles. Strong analytical and problem‑solving skills. Benefits Revenue share compensation component Health insurance Dental insurance Vision insurance Voluntary life insurance Paid Time Off Opportunities for professional development and training Access to our product and services at significant discounts and, in some instances, free Commitment to Diversity Nurp is an equal‑opportunity employer committed to fostering an inclusive and diverse workforce. We encourage applicants from all backgrounds to apply, regardless of race, color, religion, age, national origin, gender, gender identity, sexual orientation, or disability. #J-18808-Ljbffr