AI Data Trainer Finance & Quantitative Engineering

Job Title: Scientific Computing Engineer (Mathematics / Finance Domains)

Company: BespokeLabs (VC-backed; founded by IIT & Ivy League alumni)

Type: Contract | Remote

$25–$40/hour

About BespokeLabs

BespokeLabs is a venture-backed startup founded by seasoned IIT and Ivy League alumni. We specialize in developing cutting-edge, AI-driven systems and next-generation digital products. Our mission is to transform complex real-world problems into scalable, high-performance solutions powered by advanced computational science.

We are seeking exceptional Scientific Computing Engineers across two specialized domains:

1. Mathematics & Applied Math

2. Finance & Quantitative Engineering

Role Overview

As a Scientific Computing Engineer, you will design, implement, and optimize high-performance computational models and algorithms across applied math or quantitative finance. You’ll collaborate with researchers and engineers to build robust, scalable computational systems.

Key Responsibilities

Core Responsibilities (for all domains)

- Build and optimize numerical algorithms and scientific computing pipelines

- Develop high-performance code in Python, C++, Rust, or Julia

- Implement experiment workflows and validate model accuracy

- Work with simulations, numerical solvers, or statistical models

- Ensure numerical stability, reproducibility, and computational efficiency

- Collaborate with cross-functional teams to convert complex concepts into production-grade solutions.

Domain-Specific Expertise

Mathematics & Applied Math

What you’ll work on:

- PDE/ODE solvers, optimization models, simulation engines

- Computational physics, numerical analysis, Monte Carlo simulations

- Custom scientific algorithms for domain-specific workloads

Required Skills

- Strong foundations in linear algebra, calculus, probability, and optimization

- Experience with scientific computing tools (NumPy, SciPy, JAX, MATLAB, Fortran, etc.)

- Ability to build and validate custom numerical models

- Practical experience with algorithmic efficiency and accuracy checks

Finance & Quantitative Domains

What you’ll work on:

- Pricing models, risk engines, time-series forecasting

- Stochastic models, portfolio optimization, Monte Carlo simulations

- High-performance implementations of quant algorithms

Required Skills

- Background in financial mathematics, stochastic processes, econometrics

- Experience with quant libraries (Pandas, NumPy, QuantLib, etc.)

- Familiarity with option pricing, volatility modeling, or statistical forecasting

- Strong coding fundamentals and numerical precision mindset

Qualifications

- 5+ years of experience in scientific computing, applied mathematics, or quantitative engineering

- Strong programming skills in Python and one compiled language (C++, Rust, Julia, or similar)

- Experience building production-grade scientific or computational systems

- Strong grounding in numerical methods or quantitative analysis

- Prior experience in research, HPC, or computational finance is a strong plus

Bonus Skills

- GPU acceleration and parallel computing

- Distributed systems or HPC

Kaggle-like competitions or mathematical/quant challenges

- Publications, research experience, or open-source contributions

Why Work With Us?

- Work on high-impact computational systems with top-tier engineers

- Flexible remote contract role with strong compensation

- Opportunity to contribute to core R&D at a fast-growing AI startup