Data Scientist (Europe, Asia)

Remote; San Francisco (CA); Remote; USD 110,000 - 180,000; Full time

Benefits offered by this job

Remote work

28 days leave

Equipment provided

Annual retreats

Flexible core hours (10am–3pm)

Bonuses quarterly

Job summary

Sporty is seeking a Data Scientist to build and productionize data-driven ML systems that enhance personalization, search, and recommendations at scale. You will work across analytics, Python modelling, and cloud engineering in a fast-paced product environment.

You will apply advanced algorithms and data mining to improve user experience and business metrics, develop ML across domains like search ranking and content intelligence, and collaborate with stakeholders to drive measurable outcomes.

Qualifications

• Hands-on experience applying statistical and ML models to real business problems.
• Advanced Python and data analysis ecosystem.
• Strong foundation in probability, statistics, ML, and linear algebra.
• 2+ years in data science or related roles.
• Knowledge of SQL and relational databases.
• Experience with AI tools and agents in daily development.
• Degree in Applied Mathematics, Computer Science, Financial Engineering, Technology, or Engineering.
• Project and stakeholder management experience preferred.

Responsibilities

• Build personalized recommendation systems and optimize product recommendations.
• Develop and productionize ML/AI systems across domains—search ranking, recommendation, content intelligence.

Skills

Python

ML

SQL

Statistics

Probability theory

Data mining

Cloud platforms

Stakeholder management

Education

BSc in Math/CS/Engineering

Tools

Apache Spark

AI tools

Relational databases

Job description

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)