About usAt 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.
We're now preparing to launch Bigdata.com, a next-generation platform aimed at transforming financial decision-making.Join RavenPack:RavenPack is searching for a Quantitative Researcher / Data Scientist to join the Data Science - QIS Team at our Spanish headquarters.As a Quant Researcher, you will be participating in the development of new agentic workflows utilizing our semantic search engine, showcasing the value of our RavenPack data for excavating insights.
The ability to communicate effectively in English both in writing and verbally is a must.
European legal working status is required.Your Responsibilities:As a Quant Researcher, you will join the "Quantitative Investment Strategies (QIS) Team," consisting of four quant researchers dedicated to feature engineering and developing systematic trading strategies.
Your work will primarily involve data-driven research.
You will create research workflows to enhance RavenPack's reputation as a thought leader in the alternative data industry and present systematic workflows to conduct fundamental analysis.
You will work jointly with the Head of QIS on practical use cases that demonstrate the value of RavenPack data.
Additionally, your responsibilities will include:Understanding accurately the fundamental implications of a topic on the macro and microeconomy.Developing chain-of-thought agents to mimic a human professional analyst using our data, while discerning and filtering out irrelevant information.Offering data-driven insights, engaging in research discussions, and presenting features to leading financial analysts, quantitative researchers and portfolio managers in the field.Effectively communicating intricate analytical concepts to management in a clear and concise manner.What We're Looking For:A MSc in Data Analysis, Quantitative Finance, or Economics.2+ years of relevant work experience as a data scientist or quantitative researcher, manipulating large and noisy alternative datasets for features engineering.Outstanding analytical, critical-thinking, and problem-solving skills, with proven ability to conduct fundamental analysis in a systematic and quantitative way.Demonstrated proficiency in Python, and in at least Dash, StreamLit, or RepLit web applications.Strong enthusiasm for technology, and familiarity with big data technologies coupled with proficiency in language models is highly advantageous.What's in it for you?You will work with the latest technologies.Our Headquarters is located in Marbella.
Following the onboarding period, we offer a hybrid work model, allowing for up to 2 days remote per week.Free Company shuttle bus from Malaga, Fuengirola, Riviera and Estepona.You will have ownership of projects working in a collaborative environment where we will value your contribution.You will work in an agile environment able to react quickly to changes with a fairly flat hierarchy.As we encourage continuous learning, we will support your ongoing training.Diversity is in our DNA!
You will work in an international environment (over 29 nationalities and 24 languages spoken!
)We are an equal opportunity employer and value diversity at our company.
We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
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