Quantitative Finance Problem Author (Python)

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. We connect skilled contributors with cutting-edge AI work — helping you start and grow a career teaching AI by building datasets, evaluation sets, and training materials used across the industry.

This role is hired and managed by OpenTrain AI as part of ongoing efforts to create higher-quality training and evaluation materials for generative models and fine-tuning workflows.

About AI Training Work

AI training (also called data labeling, annotation, or human feedback work) is the human side of model building: people create, validate, and evaluate the examples that modern models learn from.

Contributors do remote, flexible work that ranges from designing examples and writing problem sets to validating solutions and producing evaluation ratings or fine-tuning data. Many projects need subject-matter expertise — this opening focuses on quantitative finance and computational mathematics.

The Role

You will design original, research-style, computationally intensive problem sets in quantitative finance and validate each solution with reproducible Python code and documentation.

Problems should require advanced numerical methods so they cannot be solved by simple algebraic manipulation; topics include stochastic processes, optimization, simulation, time series, and risk modeling.

• Contractor, part-time: 20+ hours per week.
• Pay-per-hour: USD $15–$60 (top listed rate $60/hr).
• Work product: problem statements, working Python code/notebooks, and clear reproducible documentation that verifies each solution.

What You'll Do

Your day-to-day will center on authoring problems and producing validated computational solutions in Python. Deliverables must include code that reproduces results and documentation describing methods, assumptions, and verification steps.

• Design original, computationally intensive quantitative finance problems (stochastic processes, simulation, optimization, time series, risk models).
• Implement and validate solutions in Python using libraries such as NumPy, SciPy, Pandas, SymPy, and relevant stats/ML packages.
• Ensure problems require advanced methods (numerical methods, Monte Carlo, optimization routines) and cannot be solved by hand.
• Provide clear, reproducible documentation (scripts or notebooks) that demonstrate and validate results.
• Produce outputs usable for text-generation examples, evaluation ratings, and fine-tuning datasets when applicable.

Requirements

We require concrete, verifiable qualifications and hands-on experience. Please read restrictions below carefully: applicants located in listed countries/territories cannot be engaged.

CV must be in English and include an email address, phone number, and a declaration of your English proficiency level.

• Bachelor’s degree or higher in finance, mathematics, statistics, or a related field.
• At least 2 years of quantitative finance or modeling experience.
• Strong Python skills and familiarity with NumPy, SciPy, Pandas, SymPy and statistics or ML libraries.
• Experience with numerical methods and simulation (e.g., Monte Carlo, PDE solvers, optimization).
• Hands-on text annotation or review experience (required).
• International or applied project experience is a plus.
• Availability for 20+ hours per week as a contractor (part-time).

Location & Acquisition Restrictions

OpenTrain engages contributors worldwide but cannot acquire services from certain locations. If you reside in any restricted location listed below you should not apply.

Restricted locations (applicants from these places cannot be engaged): Iran, Cuba, North Korea, Syria, Sudan, Venezuela, Myanmar, Russia, Belarus, Palestine, Switzerland, China, Taiwan, Kenya; US states: Alaska, Arkansas, California, Connecticut, Delaware, Georgia, Hawaii, Illinois, Indiana, Kansas, Louisiana, Maine, Maryland, Massachusetts, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, Ohio, Oregon, Tennessee, Utah, Vermont, Washington, West Virginia; and the following territories: Antarctica, Aruba, Åland Islands, Saint Barthélemy, Bonaire, Sint Eustatius and Saba, Bouvet Island, Cocos (Keeling) Islands, Democratic Republic of the Congo, Cook Islands, Christmas Island, Western Sahara, Falkland Islands (Malvinas), French Guiana, Guadeloupe, South Georgia and the South Sandwich Islands, Heard Island and McDonald Islands, British Indian Ocean Territory, Northern Mariana Islands, Martinique, New Caledonia, Norfolk Island, Niue, French Polynesia, Saint Pierre and Miquelon, Pitcairn, Réunion, Saint Helena, Ascension and Tristan da Cunha, Svalbard and Jan Mayen, Sint Maarten (Dutch part), French Southern Territories, Tokelau, United States Minor Outlying Islands, Holy See, Virgin Islands (British), Wallis and Futuna, Mayotte.

How to Apply

To apply, submit an English CV that lists your degree, relevant experience, and a clear statement of your English proficiency. Include an email address and phone number on your CV.

In your application message, state your availability (confirm 20+ hours/week) and summarize two or three recent quantitative projects (brief descriptions of your role and methods).

• Required materials: English CV with contact details and declared English proficiency.
• Optional but helpful: links to sample notebooks, GitHub, or short examples of numerical work (do not include confidential material).
• This is contract, part-time work paid per hour; production-ready Python validation and reproducible documentation are mandatory deliverables.