Job description
NovaQuant Labs is seeking a Mathematics Research Scientist to advance cutting-edge quantitative methods in finance, data science, and scientific computing. You will collaborate with cross-functional teams to develop rigorously tested models and publish impactful results. This is a hands-on role requiring deep mathematical insight, strong programming skills, and a passion for translating theory into real-world solutions. We offer a collaborative environment, competitive compensation, and opportunities for professional growth within a fast-growing analytics company.
Responsibility
- Conduct theoretical and applied research in numerical analysis, stochastic processes, optimization, differential equations, and related areas.
- Design, implement, and benchmark numerical algorithms and simulations using Python, MATLAB, Julia, and R.
- Collaborate with data science, software, and product teams to translate mathematical models into production-ready solutions.
- Validate models through backtesting, cross-validation, empirical testing, and rigorous uncertainty quantification.
- Communicate results to technical and non-technical stakeholders; contribute to technical papers and internal knowledge base.
- Mentor junior researchers and contribute to code reviews, tutoring, and research planning.
- Contribute to grant proposals, project scoping, and roadmap planning for research initiatives.
Qualification
- PhD in Mathematics, Applied Mathematics, Statistics, or a closely related field; or a Master's with substantial research and industry experience.
- Strong foundations in numerical methods, linear algebra, probability, statistics, and optimization.
- Proficiency in Python (NumPy/SciPy), MATLAB, Julia, and R; familiarity with C/C++ is a plus.
- Experience with machine learning techniques, data modeling, and computational experimentation.
- Proven ability to communicate complex mathematical concepts clearly to technical and non-technical audiences.
- Experience with high-performance computing, software development practices, version control (Git), and reproducible research.
- Track record of research impact, publications, presentations, or a strong project portfolio.