Analyst within Credit Risk Management team identifying credit segmentation opportunities using statistical methods. Collaborating with teams to enhance credit decision process and policies.
About the role
- Design and deploy end-to-end machine learning systems including NLP models, search and recommendation algorithms, and LLM-based applications.
- Build ML systems that analyze AI search behavior, identify content opportunities, and predict performance across different AI-driven platforms. Create algorithms that help brands understand and optimize for how AI agents discover and rank content.
- Collaborate with product managers to translate business requirements into technical solutions.
Requirements
- 5+ years building production machine learning systems with demonstrated business impact; strong background in NLP and search/recommendation systems required
- Deep expertise across ML approaches: classical models (XGBoost, random forests), modern deep learning architectures (transformers, graph neural networks), and reinforcement learning systems
- Proven ability to take models from research to production, including optimization for latency and cost at scale
- Experience with ML infrastructure and tooling: model serving frameworks, experiment tracking, feature stores, and monitoring systems
- Track record of technical leadership: influencing architecture decisions, improving team practices, and driving cross-functional projects without direct authority
- Excellent communication skills with ability to explain complex technical concepts to non-technical stakeholders and align ML initiatives with business outcomes
Benefits
- Equity in a fast-growing startup
- Competitive benefits package tailored to your location
- Flexible time off policy
- Generous parental leave
- A fun-loving and (just a bit) nerdy team that loves to move fast!
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Location requirements
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