Mathematics & Scientific Computing Subject Matter Expert (SME)

Innodata India; United States; Remote; USD 110,000 - 170,000; Full time

Job summary

Innodata India seeks a Mathematics and Scientific Computing SME to convert research-level mathematical methods into reliable Python problems, reference solutions, and tests. You will craft self-contained coding challenges with numerical reasoning and implement robust Python solutions using NumPy/SciPy.

The role emphasizes rigorous validation, testing, and documentation of results. Applicants should hold an MSc or PhD in a mathematical field, demonstrate strong Python skills, and have experience

Qualifications

• Strong hands-on Python programming experience.
• Ability to translate mathematical methods into correct, verifiable Python code.
• Experience critically reviewing technical or scientific code and validating numerical results.

Responsibilities

• Create and review advanced scientific coding problems for AI evaluation.
• Write correct Python reference solutions using scientific computing methods.
• Develop and debug tests including edge and ill-conditioned cases.
• Independently verify results and set justified numerical tolerances.
• Review problem specifications, formulas, code, tests and evaluation results.
• Identify issue origins in problem statements, solutions, tests, or evaluation setup.
• Check convergence behavior and ensure tests allow alternative implementations.
• Document required corrections and rerun solutions and tests before approval.

Skills

Python programming

Numerical linear algebra

Mathematical problem formulation

Code review & validation

Scientific computing

Education

MSc or PhD in Mathematics / Computational Science

Tools

NumPy

SciPy

Job description

We are seeking a Mathematics and Scientific Computing SME to develop and review advanced scientific coding problems for AI evaluation. You will turn research-level mathematical methods into reliable Python problems, reference solutions, and tests.

Key responsibilities

• Create self-contained scientific coding problems involving numerical reasoning and implementation.
• Write correct Python reference solutions using appropriate scientific computing methods.
• Develop and debug tests, including standard, edge, ill-conditioned, and failure cases.
• Independently verify expected results and establish justified numerical tolerances.
• Review problem specifications, formulas, assumptions, code, tests, and evaluation results.
• Identify whether issues originate in the problem statement, solution, tests, expected results, or evaluation setup.
• Check convergence behaviour and ensure tests allow mathematically valid alternative implementations.
• Document required corrections and rerun corrected solutions and tests before recommending approval.

Required qualifications

• MSc or PhD in Mathematics, Applied Mathematics, Computational Science, Engineering Mathematics, Financial Mathematics, or a closely related discipline.
• Advanced expertise in at least one area: numerical linear algebra, computational mechanics, computational finance, or a closely related field.
• Strong hands-on Python programming experience. Python is required for implementing and testing solutions.
• Ability to translate mathematical methods into correct, verifiable Python code.
• Experience critically reviewing technical or scientific code and validating numerical results.

Preferred qualifications

• Experience with NumPy and SciPy.
• Knowledge of iterative solvers, numerical optimization, ODE/PDE methods, finite-element methods, numerical simulation, stochastic methods, or quantitative finance.
• Experience reviewing research code, numerical software, scientific benchmarks, or computational datasets.
• Familiarity with scientific coding benchmarks is helpful but not required.