.About us At RavenPack, we are at the forefront of developing the next generation of generative AI tools for the finance industry and beyond. With 20 years of experience as a leading big data analytics provider for financial services, we empower our clients—including some of the world's most successful hedge funds, banks, and asset managers—to enhance returns, reduce risk, and increase efficiency by integrating public information into their models and workflows. Building on this expertise, we are now launching a new suite of GenAI and SaaS services, designed specifically for financial professionals. Join a Company that is Powering the Future of Finance with AI RavenPack has been recognized as the Best Alternative Data Provider by WatersTechnology and has been included in this year's Top 100 Next Unicorns by Viva Technology. You will be working on Bigdata.Com, a next-generation platform aimed at transforming financial decision-making. We're looking for We are seeking a Senior Data Scientist to join our team and drive the development and refinement of Structured Data Agents. This role requires expertise in data science methodologies, advanced Python development, and experience working with large language models (LLMs). The ideal candidate will excel in mastering new datasets, understanding their nuances, and contributing meaningfully from day one. Key Responsibilities Dataset Exploration: Rapidly understand new datasets, including corner cases and nuances, to optimize their use in AI systems. Design workflows for integrating and validating structured data. Specification & Validation: Write detailed specifications for structured data agents aligned with business goals. Design and execute testing protocols for data validation and QA, resolving inconsistencies. Development & Integration: Contribute high-quality Python code to structured data agent pipelines. Integrate LLMs for structured data processing and dynamic problem-solving. Collaboration & Communication: Work cross-functionally with Data Engineering, Product, and QA teams. Clearly explain complex technical concepts to both technical and non-technical stakeholders. Qualifications Required Skills: Proficiency in Python for data processing and AI development. Experience with LLMs, including fine-tuning and applying them to structured data. Expertise in handling large-scale structured datasets (SQL) and validation processes. Experience with cloud platforms (AWS, SnowFlake) and collaborative tools (git). Excellent communication skills and ability to contribute immediately. Strong analytical and problem-solving skills with a proactive mindset. Education & Experience: Master's degree in Data Science, Computer Science, Engineering or Finance-related fields (PhD preferred). 4+ years of experience in data science