Data Scientist

Sporty; United Kingdom; Remote; GBP 40,000 - 70,000; Full time

Job summary

A leading company in sports betting is seeking a Data Scientist to develop innovative data science solutions and machine learning models. You will work closely with various teams to tackle business challenges, contributing to the company's growth and success. Ideal candidates will have a strong background in statistics and machine learning, along with experience in Python and SQL.

Qualifications

• 3+ years of experience as a data scientist or similar role.
• Knowledge of machine learning and statistical models.
• Advanced understanding of Python and SQL.

Responsibilities

• Create data science solutions for business challenges.
• Develop advanced quantitative models like LTV and churn models.
• Collaborate with global teams to understand business requirements.

Skills

Probability theory

Inferential statistics

Machine learning

Bayesian statistics

Linear algebra

Numerical methods

Python

SQL

Education

Degree in Applied Mathematics

Degree in Computer Science

Degree in Financial Engineering

Degree in Technology

Degree in Engineering

Tools

Numpy

Pandas

Scikit-learn

LightGBM

PyTorch

Apache Spark

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 modelsParticipate in monitoring and evaluation of performance of existing modelsDevelop advanced quantitative models and concepts, such as LTV models, churn models, and recommendation enginesCollaborate with global teams of developers, traders and product developers to better understand business requirements and deliver end product to the clientsImplement and test the researched fixed income models using the risk research dataLiabilities 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 models3+ years of experience as a data scientist, quantitative researcher, quantitative analyst or another relevant roleDegree in Applied Mathematics, Computer Science, Financial Engineering, Technology or EngineeringKnowledge of probability theory, inferential statistics, machine learning, Bayesian statistics, linear algebra, and numerical methodsExperience 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, etcExperience using statistical and machine learning models to contribute to company growth efforts, impacting revenue and other key business outcomesAdvanced understanding of Python and the machine learning ecosystem in Python (Numpy, Pandas, Scikit-learn, LightGBM, PyTorch)Knowledge of SQL and experience with relational databasesAgile, action-oriente
Nice to have
Apache SparkExperience working in cloud platforms (AWS, GCP, Microsoft Azure)Relevant knowledge or experience in the gaming industry