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The Role
You will be a skilled, hands-on contributor to data science projects. You will be contributing as part of a data science team which delivers in a variety of areas across the business. This is a predominantly hands-on role, although you will be interacting with business stakeholders and there will be opportunities to take increased responsibility for deliveries as your skills develop.
The Data Science team is part of a larger data and analytics group that has separate functions for Data Analytics, BI, and Data Engineering. This structure allows the Data Science team to focus on the core data science work and solve some of the hardest problems in the business.
As an online high transaction business, Kindred Group collects a huge amount of data. This includes data about our customer's betting and game play activity, their interests and motivations, and much more. We have invested heavily in data technologies and associated analytical tools that enable our data scientists to provide innovative solutions using the latest techniques and technologies.
This role focuses primarily on commercial initiatives such as supporting our marketing, acquisition, and retention teams with state-of-the-art Data Science solutions. However, with other areas such as personalisation, fraud, cyber security, and risk management that may require Data Science expertise, there will be no shortage of opportunities to apply and improve your skills.
What You Will Do
- Hands-on contributor, applying machine learning methodologies to deliver data science projects that allow the company to achieve its goals.
- Perform data analysis and modelling on large (Tb) data sets.
- Work with senior DS and ML engineers to productionise solutions.
- Analyse a wide range of data sources to identify new business value.
- Support measurement initiatives to demonstrate the efficacy of solutions to stakeholders.
Your Experience
- Circa 1-2 years commercial experience, ideally in a data science role.
- PhD or Masters in a numerate discipline.
- Strong Python skills.
- Solid understanding of statistical modelling and machine learning/AI.
- Excellent interpersonal skills and the ability to explain complex topics to stakeholders.
- A problem-solving growth mindset with the ability to pick up new concepts quickly.
- Ideally experience putting models and processes into production.
- Ideally experience in cloud computing, in particular AWS.
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