Financial Data Scientist - Stock Intelligence

Were looking for a Data Scientist to join our Stock Intelligence team. This team specializes in delivering unique data insights on publicly traded companies, catering to the needs of the world's top hedge funds.
As a Data Scientist, you will collaborate with our Investors Team Manager within the Research and Development (R&D) department.

Why is this role so important?
data lies at the heart of everything we do. Our AI and machine learning capabilities are pivotal to our success, making this role crucial in driving innovation and delivering value to our customers. The Stock Intelligence team plays a vital role in creating actionable metrics for the financial industry, contributing significantly to our company's mission and impact.As a data scientist on the team, you will be using our proprietary raw data and products of other data teams to develop models of digital signals with strong relevance to the financials of publicly traded companies, usually businesses that rely heavily on their digital footprint. With domain expertise in the financial realm, you will suggest and explore new data sources and implement new features and bring them to production with the support of data engineers.

So, what will you be doing all day?
Your role as part of the R&D department, and as part of the investors team means your daily responsibilities may include:
● Utilize proprietary raw data and products from various data teams to develop models of digital signals relevant to the financial performance of publicly traded companies.
● Leverage domain expertise in the financial realm to identify and explore new data sources, ensuring the continuous improvement and relevance of our insights.
● Develop forecast models using advanced statistical techniques and machine learning algorithms to predict key performance indicators (KPIs) for publicly traded companies. Providing valuable insights into the digital strategies and performance of these companies.
● Collaborate with data engineers to implement new features and deploy models into production environments.
● Conduct thorough analyses to uncover actionable insights and trends within the data, providing valuable recommendations to stakeholders.
● Stay updated on industry trends, research advancements, and best practices in data science, forecasting and predictive modeling, continuously improving methodologies and techniques.
● Conduct thorough validation and testing of models to ensure accuracy, reliability, and scalability.
● Communicate findings and recommendations effectively to both technical and non-technical stakeholders, guiding strategic decision-making and driving business impact.