Company Description
We are – the Rank Group.
From the fun of Mecca Bingo to the experience of Grosvenor Casinos, from in-person to online, from local to global, players love the experiences our famous brands deliver.
This is such an exciting sector to be part of, bringing entertainment to millions in a culture of opportunity and growth.
Look at our careers site to find out more:
Job Description
We want to expand our Data Science function further within our well-established strong data-driven Centralised Analytical department. Our Data Science mission is to build machine models in the production environment relative to Marketing, Customer Insights, and Safer Gambling and establish a strong culture of data-driven decision-making in our organisation's strategy.
We are looking for a well-established Data Scientist at all levels who wants new challenges. As a Senior Data Scientist, you will work using data engineering, statistical, and ML/AI approaches to uncover data patterns and build models. We use Microsoft tech stack, including Azure Databricks (Pyspark, python), and we are expanding our data science capabilities.
To be successful in the role, you will need to have extensive experience in data science projects and have built the professional skill to understand when an approach to a project is not working, to pause and change approach.
The Data Science department is currently a smaller team, with an ambition to grow, with a mix of a Data Scientists and ML engineers. Therefore, it is an excellent opportunity to grow, contribute and challenge yourself.
We are not an isolated function, so expect to work closely with business stakeholders, data engineers, marketing analysts and BI analysts to improve our existing models, create new models, and bring our expertise.
Core Responsibilities
Apply advanced statistical techniques and ML/AI models to development and production environments Collaborate with team members and stakeholders to build data science products that enable others to make business decisions
Qualifications
Postgraduate degree in a relevant discipline ( STEM, Maths, Statistics, Physics) or equivalent experience Good data modelling, software engineering knowledge, and strong knowledge of statistical, mathematical and ML modelling are a must at this stage. Skilful in writing well-engineered code Proven experience working with ML engineers and production systems (including Cloud platforms) Proven ability to analyse large sets and experience-built ML/AI models in production with the ability to translate them into insights and actionable business recommendations Great technical and commercial communication and collaboration skills with some presentation skills Passion for learning and keeping abreast of new technologies and data models
Additional Information
#LI-IZ1 #LI-Hybrid
Join us to unlock benefits and opportunities that will boost your career journey in a vibrant, inclusive and fulfilling work environment – so you can #BeYourself
Wellbeing@Rank is important... From hybrid working and colleague support networks to menopause support and weekly PepTalks, we’re here for you.
We’ll also invest in your growth by providing development opportunities, leadership training and cutting-edge industry certifications so you have the tools and resources to help you work, win and grow with us.
Immerse yourself in new cultures and gain international exposure through our global business. Collaborate with colleagues from around the globe.
From pensions to bonus schemes, and private medical insurance to life insurance – we've got you covered.
*Our benefits vary by brand and/or location. Please have a chat with your local Talent Acquisition specialist to find out what’s in place in your location.
The Rank Group are committed to being an inclusive employer, ensuring that we better understand and meet the needs and requirements of our candidates and customers.
We aim to do this by facilitating fair and equal access to our services. If you require a reasonable adjustment to be made, please reach out to let us know ahead of your interview.
