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.