.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 AIRavenPack 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 Analyst to drive the exploration and evaluation of structured datasets, ensuring the accuracy and usability of Structured Data Agents. This role focuses on data exploration, validation, and collaboration, requiring a strong analytical mindset, attention to detail, and excellent communication skills. The ideal candidate will be adept at understanding datasets, performing in-depth evaluations, and delivering actionable insights.Key ResponsibilitiesDataset Exploration & Analysis: Rapidly explore new datasets to identify trends, anomalies, and nuances.Conduct in-depth evaluations to validate data quality and alignment with project objectives.Generate actionable insights to optimize the use of structured data in AI systems.Validation & Quality Assurance: Design and execute data validation protocols to ensure the accuracy and consistency of structured datasets.Collaborate with the development team to identify and resolve data inconsistencies and corner cases.Collaboration & Communication: Work closely with cross-functional teams, including data science, product, and engineering, to deliver high-quality outputs.Translate complex data findings into understandable insights for both technical and non-technical stakeholders.QualificationsRequired Skills: Expertise in analyzing large structured datasets (SQL) in cloud environments (Snowflake, AWS), QA processes, and anomaly identifications.Proficiency in Python for data processing and data manipulation.Familiarity with data visualization tools (streamlit) to present findings effectively.Excellent attention to detail and ability to draw insights from complex datasets.Strong communication skills to collaborate and share findings across teams.Education & Experience: Bachelor's degree in Data Science, Statistics, Computer Science, Engineering, or Finance related fields (Master's preferred).3+ years of experience in data analysis