Ds

About the role As a Data Scientist at Sporty, you will build and productionize data-driven ML systems that enhance personalization, search, and recommendation experiences, with a clear focus on measurable business impact. The role combines advanced analytics, Python-based modelling, and cloud engineering to solve real-world problems at scale in a fast-paced product environment. Our Stack • SQL • Python • AWS/Azure/GCP What you'll be doing • Utilize advanced algorithms and data mining techniques to build personalized recommendation systems, optimizing product and service recommendations to enhance user experience and improve business conversion rates. • Develop and productionize ML/AI systems across multiple domains — including search ranking, recommendation, and content intelligence — that directly impact user growth and business outcomes. What you'll bring • Hands-on experience applying statistical and ML models to real business problems, with measurable impact on revenue or key business outcomes • Advanced understanding of Python and the quantitative analysis ecosystem in Python • Strong foundation in probability theory, statistics, machine learning, and linear algebra • 2+ years of experience as a data scientist, quantitative researcher, quantitative analyst, or another relevant role • Knowledge of SQL and experience with relational databases • Proficient with AI tools and agents as part of daily development workflow; this role regularly leverages AI-assisted development to accelerate delivery • Degree in Applied Mathematics, Computer Science, Financial Engineering, Technology, or Engineering • Project and stakeholder management experience is preferred Even better if you have • Apache Spark • Experience working in cloud platforms (AWS, GCP, Microsoft Azure) • Relevant knowledge or experience in the gaming industry • Solid computer science background What’s in it for you • Sporty is a remote first company in pursuit of sustainability • A competitive salary + individual performance based bonuses every quarter • 28 days paid annual leave • Our core working hours are 10am-3pm in your local time zone with flexibility outside of this • Referral bonuses & flash bonuses • Top of the line equipment • Annual company retreats to provide great internal networking opportunities Interview Process • Remote video screening with our Talent Acquisition Team • Online home assignment • Remote video interview with Team Members (3x45 Mins) If you're interested, we encourage you to apply! Every application is reviewed by a member of our team (AI is not used in our recruitment process), and we aim to respond within 48 hours.