Senior Data Scientist

Octus delivers breaking news and market-moving intelligence through cutting-edge data and technology for hedge funds investment banks and law firms- and we’re transforming how professionals access complex and opaque information. As part of our high-performing AI Innovation team you’ll help design build and productionize modern GenAI and LLM-powered systems that support both client-facing features and internal operational efficiency. You’ll work end to end—from shaping ambiguous problems into scalable solutions to deploying reliable AI models in production - collaborating closely with product engineering and infrastructure teams. This is a hybrid role based in NYC (3 days in office per week). Curious about what we’re building? Check out our flagship GenAI product CreditAI here and our AI framework here.

Responsibilities

• Apply strong problem-solving and critical thinking skills to break down complex ambiguous requirements into clear implementable technical components and system designs.
• Design build and maintain AI-powered and data-driven systems with a focus on modern language and multimodal models including LLM-driven applications RAG pipelines and agentic workflows.
• Evaluate and productionize commercial and open-source LLMs choosing appropriate models tools and techniques for each use case. Develop multi-step agentic workflows that incorporate tools external data sources memory and control logic.
• Manage the orchestration of production LLM workflows and agentic systems ensuring reliability and efficiency through prompt routing state management retries fallbacks and error handling. Design test and iteratively refine prompts and system instructions using prompt engineering and tuning techniques to improve model reliability accuracy and task performance.
• Maintain production-grade code and services with automated monitoring and performance tracking using metrics and alerts to guide continuous improvements in models prompts and pipelines.
• Apply systems thinking to design and optimize AI and LLM systems balancing quality scalability latency cost and operational complexity while implementing efficiency improvements using model selection prompt design batching caching and retrieval strategies.
• Define and implement evaluation and observability frameworks for AI systems including automated testing task-specific benchmarks regression testing for prompts human-in-the-loop validation and performance monitoring.
• Build and integrate AI models into backend systems and APIs to support both real-time and batch inference ensuring solutions are production-ready scalable and efficient.
• Apply NLP and ML techniques to tasks such as information extraction semantic search and retrieval text classification summarization and reasoning over text and documents.
• Collaborate closely with engineering and infrastructure teams to deploy solutions using containerized and cloud-based environments (e.g. GitHub Docker AWS) applying modern deployment and infrastructure practices.
• Collaborate with product managers business stakeholders and domain experts to translate complex ambiguous business problems into actionable technical solutions and communicate progress trade-offs and outcomes to relevant stakeholders.
• Continuously learn and adapt to advancements in NLP and Generative AI to ensure solutions remain innovative and effective.

Requirements

• Bachelor’s or Master’s degree in Computer Science Engineering or a related technical field (or equivalent practical experience).
• 3+ years of experience as a Data Scientist Machine Learning Engineer or applied AI practitioner with a strong foundation in computer science algorithms and software development. 
• Advanced programming skills in Python with experience building production-grade systems beyond research or experimentation.
• Solid understanding of machine learning and applied AI concepts with experience taking solutions from prototype to production.
• Hands-on experience designing building and deploying LLM-driven or GenAI applications including familiarity with vector databases embeddings pipelines or semantic search systems.
• Practical experience with cloud-based deployments and infrastructure tools (e.g. AWS Docker GitHub) and an understanding of modern DevOps practices containerization orchestration caching strategies and cost-aware design.
• Strong problem-solving skills and systems thinking with the ability to balance trade-offs across model quality scalability inference latency cost and operational complexity.
• Ability to interpret and implement research ideas and algorithms actively contributing to research and development initiatives while translating them into production solutions.
• Excellent communication and collaboration skills with experience working closely with product managers engineers and domain experts to deliver actionable technical solutions.
• Passion for learning and staying current with the rapidly evolving AI/ML landscape including emerging best practices for GenAI applications.
• Strong ownership and initiative with the ability to independently drive projects from problem definition to delivery while being a team player and contributing to the overall success of the data science team.

At Octus we consider a range of factors in connection with compensation decisions including experience skills location and our business needs and limitations. As a result compensation may vary within and across similar roles and positions. Please note that the salary range information below is a good faith estimate for this position and actual compensation for any individual may fall outside this range if warranted by the circumstances applicable to that individual. If we identify a role that would be suitable for a broader range of skills and experience such that we would consider hiring at multiple levels then the range listed below may reflect that breadth.

The salary range estimate for this position is $130000-$145000.

The actual compensation will be at Octus’ sole discretion and will be determined by the aforementioned and other relevant factors. This position is eligible for a performance-based annual bonus.

What We Do

Octus was founded in 2013 with a simple conviction: credit decisions deserve clarity not chaos. Markets were fragmented. Intelligence was gated. Data lived in silos. Professionals were forced to stitch together incomplete pictures while the clock kept running. We built Octus to change that. Octus is the essential credit platform that tracks the entire credit lifecycle. From origination and underwriting to secondary trading refinancing distress and restructuring we follow every development across leveraged loans high-yield bonds private credit and special situations. We structure millions of documents surface risks benchmark performance and deliver expert reporting and analysis in real time. What began as a newsroom fused with legal and financial expertise has evolved into a unified ecosystem. Octus brings together proprietary data expert-driven intelligence and integrated workflow tools so credit professionals can analyze situations uncover opportunities manage portfolios execute trades and stay compliant without ever leaving the platform. Insight and action finally live in one place. Today nearly 40000 professionals across the world’s leading banks asset managers CLO managers law firms and advisors rely on Octus to move smarter and faster. They turn to us for breadth depth and rigor forged over more than a decade and for the speed integration and precision that define the future of credit workflow. Our mission is direct and ambitious: end fragmentation collapse the distance between intelligence and execution and transform insight into impact. Because in credit clarity isn’t just an advantage. It’s everything. Octus: Where credit becomes clear.

Why Work With Us

Octus is where real experts work together to cut through chaos and build clarity in credit. You feel your impact here. What you create shapes real decisions in the market. The problems matter. The people are sharp. If you want work that counts this is the place.

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