[Hiring] Senior Data Scientist at Sporty

December 19, 2023

Job Overview

  • Date Posted
    December 19, 2023
  • Location
  • Expiration date
  • Experience
    4 Years plus
  • Gender
  • hiringOrganization


Job Description

Sporty’s sites are some of the most popular on the internet, consistently staying in Alexa’s list of top websites for the countries they operate in
As a Data Scientist at Sporty, you will play a vital role in developing innovative data science solutions and machine learning models to drive business impact. Working closely with our Trading, Product, and Tech teams, you will leverage your expertise to tackle a wide range of business challenges, translating them into supervised and/or unsupervised learning problems.

Who We Are

Sporty Group is a consumer internet and technology business with an unrivalled sports media, gaming, social and fintech platform which serves millions of daily active users across the globe via technology and operations hubs across more than 10 countries and 3 continents.
The recipe for our success is to discover intelligent and energetic people, who are passionate about our products and serving our users, and attract and retain them with a dynamic and flexible work life which empowers them to create value and rewards them generously based upon their contribution.
We have already built a capable and proven team of 300+ high achievers from a diverse set of backgrounds  and we are looking for more talented individuals to drive further growth and contribute to the innovation, creativity and hard work that currently serves our users further via their grit and innovation.


  • Create data science solutions to address a variety of business challenges that can be translated to supervised and/ or unsupervised learning problems using statistical and machine learning models
  • Participate in monitoring and evaluation of performance of existing models
  • Develop advanced quantitative models and concepts, such as LTV models, churn models, and recommendation engines
  • Collaborate with global teams of developers, traders and product developers to better understand business requirements and deliver end product to the clients
  • Implement and test the researched fixed income models using the risk research data
  • Liabilities and probabilities calculations
  • Knowledge sharing and methodological supervision of more junior team members


  • Be based in Europe, Pan-Asian or Latin American Regions
  • 4+ years of experience as a data scientist, quantitative researcher, quantitative analyst or another relevant role.
  • Experience working Apache Spark
  • Experience working in AWS or similar cloud platforms (Azure GCP)
  • Advanced understanding of Python and the machine learning ecosystem in Python (Numpy, Pandas, Scikit-learn, LightGBM, PyTorch, SHAP)
  • Knowledge of SQL and experience with relational databases e.g. MySQL
  • Ability to come up with sound research designs and make methodological choices to address business problems with appropriate statistical and machine learning models
  • Ability to critically evaluate and find flaws in existing data science solutions
  • Strong knowledge of probability theory, inferential statistics, machine learning, Bayesian statistics, linear algebra, and numerical methods
  • Experience with statistical and machine learning models, such as regression-based models (e.g., logistic regression, linear regression, negative binomial regression), tree-based models (e.g., random forests), support vector machines, PCA, clustering models, matrix factorization, deep learning, etc
  • Experience using statistical and machine learning models to contribute to key business outcomes
  • Experience working on predictive algorithms within a ML environment
  • Degree in Applied Mathematics, Computer Science, Financial Engineering, Technology or Engineering

Nice to have

  • PhD or Master’s degree in applied mathematics, Computer Science, Financial Engineering, Technology or Engineering
  • Experience with Apache Airflow
  • Exposure to wider Data Science tools
  • Relevant knowledge or experience in the sports gaming industry


  • Quarterly and flash bonuses
  • We have core hours of 10am-3pm in a local timezone, but flexible hours outside of this
  • Education allowance
  • Referral bonuses
  • 28 days paid annual leave
  • 2 x annual company retreats (Lisbon + Dubai in 2022 / Phuket in Q2 2023 + 1 more TBC!)
  • Highly talented, dependable co-workers in a global, multicultural organisation
  • Payment via world class online wallet system DEEL
  • Top of the line equipment supplied by market leader Hofy
  • We score 100% on The Joel Test
  • Our teams are small enough for you to be impactful
  • Our business is globally established and successful, offering stability and security to our Team Members

Our Mission

Our mission is to be an everyday entertainment platform for everyone

Our Operating Principles

1. Create Value for Users
2. Act in the Long-Term Interests of Sporty
3. Focus on Product Improvements & Innovation
4. Be Responsible
5. Preserve Integrity & Honesty
6. Respect Confidentiality & Privacy
7. Ensure Stability, Security & Scalability
8. Work Hard with Passion & Pride

Interview Process

  • HackerRank Test
  • Remote video screening with our Talent Acquisition Team + live ID check
  • Remote 90 min video interview loop with 3 x Team Members (30 mins each)
  • Pre offer call with Talent Acquisition Team
  • ID check via Zinc & 2 References from previous employers
  • 24-72 hour feedback loops throughout process

Working at Sporty

The top-down mentality at Sporty is high performance based, meaning we trust you to do your job with an emphasis on support to help you achieve, grow and de-block any issues when they’re in your way.
Generally employees can choose their own hours, as long as they are collaborating and doing stand-ups etc. The emphasis is really on results.
As we are a highly structured and established company we are able to offer the security and support of a global business with the allure of a startup environment. Sporty is independently managed and financed, meaning we don’t have arbitrary shareholder or VC targets to cater to.
We literally build, spend and make decisions based on the ethos of building THE best platform of its kind. We are truly a tech company to the core and take excellent care of our Team Members.