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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