Data Scientist (Europe, Asia)

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. Originally posted on Himalayas