Offer summary

Qualifications:

3+ years of experience as a data scientist or in a relevant quantitative role., Degree in Applied Mathematics, Computer Science, Financial Engineering, or a related field., Strong knowledge of statistical and machine learning models, including regression and tree-based models., Proficiency in Python and experience with machine learning libraries such as Numpy and Scikit-learn..

Key responsabilities:

Develop data science solutions to address business challenges using machine learning models.

Monitor and evaluate the performance of existing models and implement improvements.

Collaborate with global teams to understand business requirements and deliver effective solutions.

Create advanced quantitative models, such as churn models and recommendation engines.

Job description

We consistently top the charts as one of if not the most used Sports Betting website in the countries we operate in.

With millions of weekly active users, we strive to be the best in industry for our users.

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.

Responsibilities

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

Requirements

Ability to come up with sound research designs and make methodological choices to address business problems with appropriate statistical and machine learning models

3+ years of experience as a data scientist, quantitative researcher, quantitative analyst or another relevant role

Degree in Applied Mathematics, Computer Science, Financial Engineering, Technology or Engineering

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 company growth efforts, impacting revenue and other key business outcomes

Advanced understanding of Python and the machine learning ecosystem in Python (Numpy, Pandas, Scikit-learn, LightGBM, PyTorch)

Knowledge of SQL and experience with relational databases

Agile, action-oriente

Nice to have

Apache Spark

Experience working in cloud platforms (AWS, GCP, Microsoft Azure)

Relevant knowledge or experience in the gaming industry

Benefits

Quarterly bonuses

We have core hours of 10am-3pm in a local timezone, but flexible hours outside of this

Top-of-the-line equipment

Referral bonuses

28 days paid annual leave

Annual company retreat

Highly talented, dependable co-workers in a global, multicultural organisation

Payment via DEEL, a world class online wallet system

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

Online HackerRank Test (Max time of 90 Minutes)

Remote video screening with our Talent Acquisition Team

Remote video interview with 3 x Team Members (45 mins each, not separate days)

24-72 hour feedback loops throughout process

Post Interview Process

Feedback call on successful interview

Offer released followed by contract

ID Check Via Zinc & 2 references from previous employers

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.

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