Wall Street Football vision is to lead the data-centric and tech-centric revolution that will disrupt every aspect of sports. We build technologies that valorise sports data in order to connect all sports related services from media and sport analytics, to fan engagement and sport betting.
Wall Street Football is operating in different industries through a plurality of product teams that work synergically. The current opening is for our new Sport Analytics team, building products to support Multi Club Ownership and Football Clubs in the introduction of a new data-drive way to manage the club and the scouting of football players.
What are we looking for
We are seeking a talented and experienced Software Engineer with a strong interest in Data Science to join our sport analytics team and help us build the foundations of the tech infrastructure of our sport analytics business.
You will collaborate within a comprehensive cross-functional team to construct the platform from the ground-up, integrating external data providers and employing advanced analytics and modeling techniques.
This is a remote working opportunity.
Key Responsibilities
– Integrate data from various sources such as external APIs and third-party data providers.
– Work alongside data engineers to support the development and deployment of data pipelines.
– Apply data science techniques to extract insights and patterns from large datasets.
– Collaborate with data scientists to integrate machine learning models and algorithms into decision making tools.
– Utilize tools like D3.js, Tableau, or other visualization libraries to enhance user understanding of complex datasets and drive decision makers.
– You will have the chance to be an active participant in product discussions and decisions in a fast-paced and quickly growing environment.
Key qualifications
Must have
– Experience in software development in Python, SQL querying and Bash scripting.
– Familiarity with software engineering principles and best practices, including but not limited to testing, writing clean code, data modeling, and employing design patterns.
– Familiarity with web scraping techniques.
– Strong understanding of data science concepts and methodologies.
– Knowledge of machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch)
Nice to have
– Familiarity with integrating sport data providers such as Wyscout, Opta and StatsBomb.
– Experience with big data technologies (e.g. Spark, Google BigQuery, Databricks).
– Experience with Tableau or similar visualization libraries.
– Exposure to agile development methodologies.
– Passion about sports and game analytics
To apply send your CV at : info@wallstreetfootball.io
