Yuma Holdings, LLC
Join Us in Shaping the Future of Decentralized Intelligence
At Yuma, we are on a mission to drive positive economic and societal change by revolutionizing the way the world connects through decentralized intelligence. Yuma exists to champion development on Bittensor, an ecosystem that empowers brilliant minds and democratizes access to advanced computing and intelligence. Together we are cultivating a space where innovation thrives, ideas are rewarded, and cutting‑edge technology becomes accessible to everyone.
As a proud subsidiary of DCG, a global investor, builder, and incubator, we have the backing and resources to empower the next generation of visionaries. Our role is clear: to support and nurture transformative teams at the critical early stages of development. By removing barriers and providing the tools needed to succeed, we’re ensuring that the AI revolution is not just for a select few but for the visionaries shaping our shared future.
About the Role
As a Quantitative Researcher at Yuma, you’ll contribute to the research and development of on‑chain trading strategies within the Bittensor ecosystem. This is a hands‑on opportunity to apply statistical and machine‑learning techniques to blockchain data, uncover market inefficiencies, and support the design of alpha‑generating models. You’ll work closely with the Investment Lead and engineering teams to explore alpha signals, build prototypes, and help refine strategies for live deployment. This role is ideal for someone with strong modeling skills and a passion for decentralized markets. Key Responsibilities
Analyze blockchain data to uncover predictive signals and short‑term market inefficiencies Apply statistical and machine‑learning techniques to develop models for alpha generation Prototype and evaluate signal performance across TAO and Subnet token markets Support the design of portfolio allocation frameworks based on model outputs and market dynamics Contribute to risk analytics by analyzing volatility, drawdowns, and exposure across strategies Assist in monitoring live strategy performance and refining model parameters Build internal libraries and tooling for machine‑learning–based strategy components Support the development of backtesting frameworks to evaluate strategy effectiveness Collaborate with Engineering to ensure data pipelines are aligned with research needs Contribute to the design and maintenance of trading infrastructure Skills
Brilliant analytical and problem‑solving skills Excellent statistical modeling and machine‑learning skills Required Qualifications
Bachelor's or Master’s degree in Math, CS, Stats, Physics, or related field 1–2 years of experience in quantitative research, data science, or trading analytics Proven interest in financial markets and trading strategies Creative, self‑driven, and highly detail‑oriented Strong communicator and collaborative team player Preferred Qualifications
Prior experience applying machine‑learning algorithms on noisy, real‑world datasets Exposure to signal generation workflows and quantitative research pipelines Proficiency with modern ML frameworks such as PyTorch, TensorFlow, or equivalent Familiarity with blockchain data and DeFi protocols Benefits
An opportunity to thrive in a dynamic, cutting‑edge environment at a rapidly scaling company led by experienced industry leaders An innovative learning environment where you can immerse yourself in the latest technologies, contribute to building a transformative new industry, and make a meaningful impact Competitive base salary, bonus, and incentive compensation Unlimited PTO / Flexible time off – work with your leader to take time off when you need it Professional development budget with flexibility for personal and professional growth Outstanding health insurance for employee, partner, and dependents Life insurance, short‑term & long‑term disability coverage 401(k) plan with company contribution Flexible spending programs for medical and dependent care Paid parental leave Equal Opportunity Employer
Yuma is an Equal Opportunity Employer and embraces diversity. We do not tolerate discrimination or harassment based on race, color, religion, marital status, gender (including pregnancy, childbirth or related medical conditions), gender identity, sexual orientation, parental status, national origin, age, disability, genetic information (including family medical history), political affiliation, military service, or any other non‑merit‑based factors protected under federal, state or local law. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, transfer, leaves of absence, compensation, and training. Self‑Identification Policy
For government reporting purposes, we ask candidates to respond to a self‑identification survey. Completion of the form is entirely voluntary and will not be considered in the hiring process. Any information you provide will be recorded and maintained in a confidential file.
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As a Quantitative Researcher at Yuma, you’ll contribute to the research and development of on‑chain trading strategies within the Bittensor ecosystem. This is a hands‑on opportunity to apply statistical and machine‑learning techniques to blockchain data, uncover market inefficiencies, and support the design of alpha‑generating models. You’ll work closely with the Investment Lead and engineering teams to explore alpha signals, build prototypes, and help refine strategies for live deployment. This role is ideal for someone with strong modeling skills and a passion for decentralized markets. Key Responsibilities
Analyze blockchain data to uncover predictive signals and short‑term market inefficiencies Apply statistical and machine‑learning techniques to develop models for alpha generation Prototype and evaluate signal performance across TAO and Subnet token markets Support the design of portfolio allocation frameworks based on model outputs and market dynamics Contribute to risk analytics by analyzing volatility, drawdowns, and exposure across strategies Assist in monitoring live strategy performance and refining model parameters Build internal libraries and tooling for machine‑learning–based strategy components Support the development of backtesting frameworks to evaluate strategy effectiveness Collaborate with Engineering to ensure data pipelines are aligned with research needs Contribute to the design and maintenance of trading infrastructure Skills
Brilliant analytical and problem‑solving skills Excellent statistical modeling and machine‑learning skills Required Qualifications
Bachelor's or Master’s degree in Math, CS, Stats, Physics, or related field 1–2 years of experience in quantitative research, data science, or trading analytics Proven interest in financial markets and trading strategies Creative, self‑driven, and highly detail‑oriented Strong communicator and collaborative team player Preferred Qualifications
Prior experience applying machine‑learning algorithms on noisy, real‑world datasets Exposure to signal generation workflows and quantitative research pipelines Proficiency with modern ML frameworks such as PyTorch, TensorFlow, or equivalent Familiarity with blockchain data and DeFi protocols Benefits
An opportunity to thrive in a dynamic, cutting‑edge environment at a rapidly scaling company led by experienced industry leaders An innovative learning environment where you can immerse yourself in the latest technologies, contribute to building a transformative new industry, and make a meaningful impact Competitive base salary, bonus, and incentive compensation Unlimited PTO / Flexible time off – work with your leader to take time off when you need it Professional development budget with flexibility for personal and professional growth Outstanding health insurance for employee, partner, and dependents Life insurance, short‑term & long‑term disability coverage 401(k) plan with company contribution Flexible spending programs for medical and dependent care Paid parental leave Equal Opportunity Employer
Yuma is an Equal Opportunity Employer and embraces diversity. We do not tolerate discrimination or harassment based on race, color, religion, marital status, gender (including pregnancy, childbirth or related medical conditions), gender identity, sexual orientation, parental status, national origin, age, disability, genetic information (including family medical history), political affiliation, military service, or any other non‑merit‑based factors protected under federal, state or local law. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, transfer, leaves of absence, compensation, and training. Self‑Identification Policy
For government reporting purposes, we ask candidates to respond to a self‑identification survey. Completion of the form is entirely voluntary and will not be considered in the hiring process. Any information you provide will be recorded and maintained in a confidential file.
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