Senior Quantitative Data Analyst

Betsson; Greater London; In loco; GBP 90.000 - 130.000; Tempo pieno

Vantaggi offerti da questo lavoro

Competitive salary

Benefits package

Dynamic team

Descrizione del lavoro

The Wow in the United Kingdom is seeking a Senior Quantitative Analyst to develop and maintain cutting-edge statistical models for sports betting. You will drive risk management, price micro-markets and derivatives, and push data-driven innovations across the business.

You will collaborate with data engineers and performance analysts to enhance models, deploy scalable solutions, and mentor teammates in quantitative methods.

Competenze

• PhD, Masters or Bachelor’s degree in a STEM field (e.g., Mathematics, Statistics, Computer Science, Physics, Engineering).
• Proficiency in C# and Python is essential.
• Strong knowledge of statistical and machine learning modelling techniques.
• Excellent communication skills to explain complex concepts to diverse audiences.
• Solid understanding of the sports betting industry, sports trading, and sports modelling.

Mansioni

• Develop and refine core sports betting models using statistical methods, ML, and AI techniques.
• Build and maintain player statistics models to predict performance and betting markets.
• Design and implement risk models to optimize exposure and ensure sustainability.
• Contribute to market expansion with derivatives and micro-markets through underlying modeling.
• Collaborate on modernizing modelling technologies and data-driven methodologies.
• Document model methodologies clearly for technical and non-technical stakeholders.

Conoscenze

C#

Python

Statistical modelling

Machine learning

Data retrieval

Communication skills

Formazione

Bachelor's / Master's / PhD in STEM

Strumenti

SQL

Descrizione del lavoro

The Wow

Senior Quantitative Analyst - Revolutionizing Sports Betting

Join our team and shape the future of sports betting! We're seeking a highly motivated and innovative Quantitative Analyst to develop and maintain cutting-edge statistical models. You'll play a crucial role in enhancing our market offerings and driving our success in the dynamic world of sports betting. This is an opportunity to leverage your expertise in data science, machine learning, and AI to build models that predict outcomes, manage risk, and unlock new possibilities in micro-markets and derivatives.

A taster of what you will be involved with:

As a Senior Quantitative Analyst, you will be a key contributor to our quantitative modelling strategy across multiple areas, including:

• Core Sports Betting Models: Develop and refine models for predicting match outcomes, incorporating advanced statistical methods, machine learning algorithms, and AI techniques.
• Player Statistics Models: Build and maintain sophisticated models that analyses player performance and predict individual contributions, opening up exciting new betting markets.
• Risk Management Models: Design and implement robust risk models to optimize our exposure and ensure the long-term sustainability of our operations.
• Market Expansion: Contribute to the development of innovative market offerings, including derivatives and micro-markets, by creating the necessary underlying models.
• Technology Modernization: Collaborate on the modernization of our modelling technologies, exploring and implementing new tools and platforms to enhance efficiency and scalability.
• Data-Driven Innovation: Contribute to the development of new data-driven methodologies, pushing the boundaries of what's possible in sports betting analytics.
• Data Collaboration: Work closely with the data engineering team to optimize data storage and retrieval processes, ensuring seamless access to the information needed for model development.
• Data Acquisition: Identify and collect relevant data sources to fuel model development and improvement.
• Knowledge Sharing: Document model methodologies clearly and concisely, effectively communicating complex technical concepts to both technical and non-technical stakeholders across the business.
• Performance Analysis: Collaborate with the performance analysis team to identify areas where models can be improved and contribute to the ongoing refinement of our analytical tools.

What we are looking for

You are a highly analytical and results-oriented individual with a passion for sports and a deep understanding of quantitative modelling. You thrive in a fast-paced environment and are eager to contribute to a team that is pushing the boundaries of sports betting analytics.

• Education: PhD, Masters, or Bachelor’s degree in a STEM field (e.g., Mathematics, Statistics, Computer Science, Physics, Engineering).
• Programming Skills: Proficiency in C# and Python is essential.
• Modelling Expertise: Strong knowledge of statistical and machine learning modelling techniques.
• Communication Skills: Excellent communication skills, with the ability to clearly explain complex technical information to diverse audiences.
• Industry Knowledge: A solid understanding of the sports betting industry, sports trading, and sports modelling.
• Problem-Solving: Demonstrated ability to solve complex problems and provide clear justifications for chosen methodologies.
• Modelling Experience: Proven experience in building and deploying mathematical models.
• Data Skills: Proficient in data retrieval and statistical analysis.
• Experience: 5+ years of experience in a quantitative role.

Bonus Points:

• Experience working in the sports betting industry.
• Mentoring and team leadership skills.
• Experience developing quantitative models using machine learning and AI.
• Strong knowledge and skills in data engineering (SQL).

What we offer

• A chance to be part of a dynamic and innovative team at the forefront of the sports betting industry.
• The opportunity to work on challenging and impactful projects.
• A competitive salary and benefits package.
• A collaborative and supportive work environment.

If you're ready to take your quantitative skills to the next level and revolutionize the world of sports betting, we encourage you to apply!

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