Additionalinformation

Additional Information

• Sourcing, cleaning, and validating diverse datasets from various internal and external sources.
• Conducting in-depth exploratory data analysis to uncover hidden patterns, identify trends, and generate actionable insights that inform strategic business decisions.
• Developing and deploying robust statistical and machine learning models to address complex business challenges and drive innovative solutions.
• Designing, implementing, and analysing A/B tests and other controlled experiments to measure the impact of new features, strategies, or models.
• Contributing to the development and maintenance of scalable data science infrastructure.
• Partnering closely with stakeholders to understand key business goals and translate them into effective, data-driven solutions.
• Communicating complex findings and insights to technical and non-technical audiences through visualisations, reports, and presentations.
• Researching and championing innovative data science techniques, tools, and methodologies.
• Fostering a culture of continuous learning and innovation within the wider Data Analytics team.

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At bet365, we're committed to creating an environment where everyone feels welcome, respected and valued. Where all individuals can grow and develop, regardless of their background. We're Never Ordinary, and we're always striving to be better. If you need any adjustments or accommodations to the recruitment process, at either application or interview, please don’t hesitate to reach out.

Companydescription

Company Description

We’re one of the world’s leading online gambling companies, revolutionising the industry since 2000. Founded by Denise Coates CBE, we now employ over 10,000 people and serve over 120 million customers in 26 languages. We empower our employees to push boundaries and explore new ideas, cultivating a culture that celebrates and rewards creativity. This offers employees a wealth of growth opportunities, giving them the opportunity to make a real impact in the world of online gambling. As a forward-thinking company, we’re breaking new ground in software innovation too, redefining what’s possible for our global worldwide. Our focus on In-Play betting has solidified our market-leading position, featuring more than 1.38 million In-Play sporting events a year. With over 750 concurrent sporting fixtures at peak and more live sports streamed than anyone else in Europe (750,000), we handle over 6 million HTTP requests daily and process more than 1.5 million bets per hour at peak.

Jobdescription

Job Description

As a Data Scientist, you will develop machine learning solutions and perform statistical analysis to inform strategic, data-driven business decisions and initiatives.

Our Data Analytics team monitors, analyses, and optimises key performance indicators across our range of Sports and Gaming products. We are looking for a talented Data Scientist to join us and help turn complex data into clear, actionable insights.

In this role, you will be instrumental in extracting valuable insights from vast datasets, developing predictive models, and contributing to data-driven decision-making across various business functions.

Collaborating with stakeholders from areas such as Fraud, Responsible Gambling, Trading and Branding allows us to identify opportunities, solve complex problems, and build robust data solutions. This is an exciting opportunity to apply cutting-edge data science techniques in a fast-paced, high-volume, and globally recognised industry, utilising a modern and powerful tech stack. This role is eligible for inclusion in the Company’s hybrid work from home policy.

Qualifications

• Excellent analytical, problem-solving, and critical thinking skills.
• PhD degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
• Experience using core machine learning techniques, such as regressions, classification, clustering and deep learning.
• Strong programming skills in languages such as Python, R, SQL.
• Familiarity with data science libraries and frameworks.
• Detailed understanding of data mining, data warehousing, and data visualisation techniques.
• Knowledge of Artificial Intelligence and its use within data science.
• Strong communication skills with both technical and non-technical audiences.
• Knowledge of cloud computing, distributed systems, and big data technologies.