Research & Development Manager - Sport Modelling #LI-ML1 #LI-Hybrid

Kindred Group is a place where technology professionals can reach career aspirations in a supportive and inclusive environment. Ranking in the top 25% of the consumer industry for Engagement and 2nd in the Gambling Industry All-Index for Diversity & Inclusion, we take pride in our working environment, our people and culture. 

As a part of the wider Analytics function, the Quant Team works closely with the Data Science team, delivering a truly innovative and unparalleled experience for the customers of our sportsbook brands. We are a small but growing team, split into two disciplines: Research and Development, and Quant Engineering. The work of the team involves writing high-quality, containerised software, primarily in Python, making use of a variety of data technologies, including PostgreSQL in particular. 

As a Quant Research and Development Manager you will bring predictive sports modelling experience, to lead a small group (between 3 and 5 colleagues) within the Research and Development team. You will manage the delivery of models and algorithms that underpin the vision of algorithm-assisted trading within the Kindred Sportsbook Platform (KSP).  You will balance management with hands-on research and development responsibilities, working closely with Quant Engineers to deliver models through the whole Quant lifecycle.

Responsibilities 

• Take ownership of Quant Team Research and Development projects by providing technical expertise and managing Quant Analyst and other resources. 
• Manage the delivery of Research and Development work on a week-to-week basis, and work with the Quant Research and Development Lead to plan quarterly work focuses and longer-term roadmaps. 
• Research, develop and assess probabilistic pricing models for sporting events. 
• Research, develop and assess strategies and tools to assist commercial, operational and trading functions in offering odds to customers. 
• Analyse and prepare data and assist with data quality for use in probability models and tools. 
• Work closely with Quant Engineers to build and deploy solutions as production services and data products that meet defined business needs. 
• Write high-quality code that follows best practices and facilitates collaboration and re-usability by other team members. 
• Drive measurement initiatives to ensure quant processes and algorithms are measured and iterated to deliver value. 
• Promote work and contributions for use within the team and the wider business, through global collaboration, conversations, written reports, and presentations. 
• Line-manage a team of 3-5 people made up of Quant Analysts, Quant Data Analysts and potentially, in time, Quant Engineers. 
• Contribute to recruitment efforts. 

Expected Attributes 

• Experience in applying statistical or machine learning modelling techniques to sporting events, with familiarity with some of the existing literature for modelling sport. 
• Commercial experience in a related role, including experience mentoring less experienced colleagues or team members. 
• Ability to provide constructive coaching and mentoring and to professionally develop line reports. 
• Confidence to take the lead in decision making and prioritisation. 
• Excellent programming skills in Python, using numerical and scientific libraries such as Numpy and Scipy and a good knowledge of SQL. 
• Excellent skills manipulating, exploring and analysing varied data sets and data pipelines, including with libraries such as pandas. 
• Experience applying software development best practices such as version control, unit testing, linting and CI/CD and an understanding of software design patterns. 
• Experience with cloud computing, ideally AWS. 
• Excellent communication ability, both written and verbal, able to explain complex topics to non-specialists 
• A problem-solving growth mindset with the ability to pick up new tools and concepts quickly 
• Open-mindedness, able to interact in a constructive manner with the Quant team, stakeholders and other contributors to Quant solutions. 
• Ability to deal with and account for uncertainty, with the flexibility to learn by iteration. 
• Ability to appropriately manage time between operational and management responsibilities. 

It would be great if you also have:

• A Master's degree or PhD in STEM subject. 
• Experience with Bayesian inference, state-space models, multivariate time-series modelling and causal inference. 
• Experience with widely used probabilistic programming and machine learning libraries such as Stan, PyMC3, Edward, Scikit-Learn, Keras, Tensorflow, PyTorch or MLib. 
• Programming skills in a statically typed language such as Scala, C++, Rust or Java. 
• An interest in sports betting. 
• Over 3 years relevant commercial experience.

What do we offer?  

⚡ A great team of passionate analysts and engineers. 

🌍 Mix of 60+ nationalities and Swedish culture in an English-speaking environment. 

🌆 Awesome offices with ergonomic desks, pool and table tennis tables, VR area, gym and yoga area, subsidised lunch, free breakfast on Thursday, daily fresh fruit. 

🛫 25 days paid vacation plus bank holidays. 

🌳 3 days CSR leave. 

📈 Employee share plan. 

📗 Training budget, conferences, access to LinkedIn Learnings and mentoring programmes. 

⚕️ Private medical insurance & life assurance. 

👶 Enhanced maternity, paternity, and shared parental leave. 

🚲 £300 Wellbeing allowance. 

💱 Up to 8% matched pension contributions. 

🏡 Flexible working. 

💼 Occasional travel to other Kindred Group offices including Stockholm, Malta, Gibraltar & Madrid. 

☕ Meetups and calendar of social events in the office; quarterly Analytics socials. 

Application Process  

Click on the "Apply Now" button and complete the short web form. Please add a covering letter in English to let us know your motivation for applying and your salary expectation. Our Talent Acquisition team will be in touch soon.

Kindred is an equal opportunities employer committed to employing a diverse workforce and an inclusive culture. As such we oppose all forms of discrimination in the workplace. We create equal opportunities for all our applicants and will treat people equally regardless of, and not limited to, gender, age, disability, race, sexual orientation. We are committed not only to our legal obligations but also to the positive promotion that equal opportunities bring to our operations as set out in our sustainability framework.

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