FREE ACCESS
5,000–10,000 jobs/day
See all jobs on Scoutfield
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and deploying AI systems, with a strong focus on quantitative research and development. Proficient in Python and experienced in creating reliable production systems that meet enterprise requirements for security, performance, and data governance.
Highest-signal resume keywords
Quantitative Research ExperienceAI Application DevelopmentHigh Proficiency In PythonEnterprise Production RequirementsTechnical Communication Skills
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Quantitative ResearchAI Systems DevelopmentPython ProgrammingData WorkflowsStatistical EvaluationMachine Learning SystemsDebuggingArchitecture DesignProduction EngineeringIntegration
Soft Skills
Technical JudgmentCommunication Across TeamsEnd-To-End OwnershipProblem SolvingCollaboration
Tools & Technologies
LLMsResearch ToolsEvaluation HarnessesProduction AcceleratorsObservability ToolsData Governance Tools
Industry Keywords
Quantitative InvestmentTrading FirmsCustomer WorkflowsMeasurable Business OutcomesSecurityPrivacyCost Management
Tech Stack
Tools & technologiesPython
About the role
Key responsibilities & impact- Partner directly with quantitative investment and trading firms to identify opportunities across research, data analysis, and software development
- Translate customer needs into practical implementations, evaluations, and measurable outcomes
- Design, build, and deploy AI systems that solve customer problems and produce measurable business outcomes
- Build prototypes, evaluation harnesses, reference implementations, integrations, and production accelerators
- Make technical decisions across models, agents, retrieval, tools, data, reliability, observability, latency, cost, safety, security, and governance
- Diagnose implementation challenges, reproduce failures, test hypotheses, and resolve blockers
- Help customers progress from prototypes to reliable production systems, sustained adoption, and scaled impact
- Lead technical workshops and hands-on sessions for quantitative researchers and engineers
- Translate deployment experience, evaluations, and feedback into requirements for Product, Research, and Engineering
- Create reusable architectures, tooling, playbooks, and technical guidance for future enterprise deployments
Requirements
What you’ll need- Experience in quantitative research, quantitative development, or a closely related role, or excellent understanding of quantitative investment and trading teams
- Practical, hands-on experience with LLMs or building AI applications
- Substantial personal contributions in code, architecture, evaluation, debugging, or production engineering
- High proficiency in Python
- Experience building and debugging research tools, data workflows, or software systems
- Rigorous approach to evaluating quantitative, statistical, or machine-learning systems
- Experience with enterprise production requirements including integrations, reliability, observability, security, privacy, data governance, performance, and cost
- Ability to connect technical decisions to customer workflows, adoption, and measurable business outcomes
- Ability to communicate across engineers, technical leaders, security teams, product leaders, and executives
- Ability to work with high agency, technical judgment, and end-to-end ownership in ambiguous environments
Benefits
Comp & perks- Relocation assistance to new employees
- Hybrid work model
- Immigration and sponsorship support may be provided based on individual circumstances