3 дня назад
Staff AI Research Scientist (Fintech)
209 500 - 283 500$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Staff AI Research Scientist (probabilistic modeling/LLM reasoning): Advancing AI research for decision-making under uncertainty and developing interpretable, trustworthy reasoning systems for fintech products with an accent on probabilistic modeling, causal inference, simulation-based planning, and reinforcement learning. Focus on enabling LLMs to reason over structured business data, translating research into decision-support capabilities, and defining long-term research programs.
Location: Mountain View, California, United States
Salary: $209,500–$283,500 base pay, with potential cash bonus, equity rewards, and benefits.
Company
is a financial technology platform serving approximately 100 million customers through products including TurboTax, Credit Karma, QuickBooks, and Mailchimp.
What you will do
- Conduct basic and applied research on probabilistic, causal, and simulation-based models.
- Develop methods that enable large language models to reason over structured business data.
- Define long-term research goals aligned with products and establish intermediate milestones.
- Translate scientific AI methods into decision-support capabilities with designers, product managers, engineers, researchers, and legal experts.
- Engage with the academic and research community through publications, presentations, open-source work, and collaborations.
- Mentor junior researchers, AI scientists, and interns through goal setting and technical guidance.
Requirements
- PhD in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, or a related field focused on AI, machine learning, or data science.
- At least 5 years of relevant post-PhD work experience and at least 8 years of theoretical or applied research experience.
- Established publication record, preferably including first-author papers at top-tier AI conferences such as NeurIPS, ICML, ICLR, KDD, ACL, or AAAI.
- Experience defining and leading research projects and communicating technical ideas through publications, presentations, and open-source work.
- Hands-on Python development and debugging with TensorFlow, PyTorch, or similar frameworks.
- Deep expertise in machine learning, including areas such as probabilistic modeling, causal inference, time-series forecasting, reinforcement learning, agentic and multi-agent systems, neuro-symbolic AI, deep learning architectures, or model training.
Nice to have
- Experience leading a research team and mentoring junior colleagues.
Culture & Benefits
- Collaboration with domain experts, data scientists, machine learning engineers, and cross-functional stakeholders.
- Opportunities to influence ’s AI strategy and contribute to emerging technologies and products.
- Competitive compensation with performance-based rewards.
- Potential eligibility for cash bonuses, equity rewards, and employee benefits.
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