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.
We're now preparing to launch Bigdata.com, a next-generation platform aimed at transforming financial decision-making.
Join RavenPack: RavenPack is seeking a skilled Data Scientist to join our Data Science Factor Team at our Spanish headquarters.
In this role, you will play a pivotal part in supporting the validation of new data products and LLM-driven agents, while also contributing to the productization of innovative factors and workflows.
Your focus will include developing proof-of-concept applications that enhance the usability and effectiveness of our data solutions.
Your Responsibilities: Collaborate with a diverse team of data scientists and engineers to develop and refine innovative data products, ensuring they meet the highest standards of quality and relevance.
Engage in the design and implementation of data pipelines that facilitate the extraction, transformation, and loading (ETL) of structured and unstructured data for analysis and modeling.
Validate and assess the outputs from the Data Science Research Team, ensuring that the data products are robust, accurate, and aligned with business objectives.
Conduct data quality checks and implement validation processes to maintain the integrity of data throughout the product life-cycle.
Share insights and findings with both technical and non-technical stakeholders, contributing to a culture of knowledge sharing and continuous improvement.
Document processes and methodologies related to data science and engineering practices, promoting transparency and best practices within the team.
What We're Looking For: Bachelor/MSc in a quantitative field such as Data Science, Computer Science, Engineering, Applied Mathematics, or a related discipline Strong analytical, quantitative, and problem-solving skills, with a proven track record of applying these skills in real-world scenarios.
Proficiency in programming languages such as Python, with experience in developing data processing pipelines and utilizing libraries for data analysis.
Familiarity with SQL and experience working with relational databases knowledge of NoSQL databases is a plus.
Experience in implementing data quality checks and validation processes, ensuring data integrity and reliability.
Strong communication skills, with the ability to articulate complex concepts clearly and effectively to diverse audiences.
Desired Skills: Familiarity with cloud platforms (e.g., AWS) and experience with data engineering tools and technologies.
Practical experience with Natural Language Processing (NLP) and large language models (LLMs).
Exposure to big data technologies and frameworks, as well as familiarity with machine learning techniques and agentic workflows.