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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.

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