Job Description

Job Title: Data Scientist

Location: New Jersey (Onsite from Day 1) - Only local candidates

Job Type: Long-term contract

Key Responsibilities

• Formulate complex optimisation problems (nonlinear, nonconvex, stochastic, constrained, multi-objective).
• Build advanced optimisation pipelines using:
• SciPy Optimise, PySwarms, mystic, pymoo, Bayesian Optimisation.
• Develop custom, complex solvers and hybrid algorithms leveraging open-source optimisation frameworks.
• Implement objective functions, constraint models, surrogate models, and penalty formulations.
• Integrate optimisation techniques into ML workflows (hyperparameter tuning, black-box optimisation, surrogate modelling).
• Conduct convergence, sensitivity, robustness, and stability analysis of optimisation methods.
• Scale optimisation systems using Python, distributed computing, and numerical acceleration.
• Communicate complex mathematical concepts to cross-functional audiences.

Required Qualifications

• Master's/PhD in Operations Research, Applied Mathematics, Computer Science, Engineering, or related quantitative field.
• Expertise in nonlinear, global, evolutionary, and multi-objective optimisation (e.g., NSGA-II/III, CMA-ES, DE).
• Strong knowledge of Bayesian Optimisation and Gaussian Process modelling.
• Deep mathematical foundation (numerical methods, probability, linear algebra).
• Proficiency in the Python scientific ecosystem (NumPy, SciPy, pandas, scikit-learn).
• Demonstrated ability to design custom solvers for high-dimensional, ambiguous, or poorly behaved optimisation landscapes

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