Address
Form of workThe Opportunity
As our Senior Data Scientist, you will play a crucial role in helping us achieve our goals and deliver success on behalf of our customers by building advanced statistical models and algorithms that infer and predict individual customer behaviours in real-time, based on retail, online and ecommerce transaction data. This is an exciting opportunity to collaborate with the wider Data and Analytics team.
This is a hybrid role based in our Cambridge or London office, so you will ideally be comfortable coming into the office once or twice a week. If you’re interested in the role but require more flexibility, please speak to us!
Day to Day
- Manage the delivery of advanced statistical models and algorithms that infer and predict individual customer behaviours in real-time, based on retail, online and ecommerce transaction data
- Coach and support junior team members through technical leadership
- Contribute to improvements in data science products and process by collaborating with Engineering, Product, and Research teams
Analytics & Data Science at Featurespace
Find out what it’s like to be part of the team!
About you
Must haves:
- Good degree in a scientific or numerate discipline, e.g., Computer Science, Physics, Mathematics, Engineering, or equivalent experience
- Proven client facing skills, and an ability to communicate complex analytical concepts to a variety of audiences, especially in a data science context. This includes the application of practical machine learning algorithms to real-world data
- Depth of experience in stakeholder management and managing customer expectations and common challenges
- Experience working with customers to gather complex sets of requirements including analytical system design, data integration design, and model design
- Ability to manage and prioritise changeable workload, ensuring internal and external deadlines are met
- Knowledge of Python and familiarity with SQL
- Knowledge of fundamental machine learning concepts (feature engineering, algorithms, model evaluation, model bias, etc.)
Great to haves:
- Experience in deploying statistical models and analytical algorithms in industry
- Experience with software engineering, version control, and the Unix command line
- Practical experience of the handling and mining of large, diverse, data sets
- Industry experience in financial services, fraud, and fraud strategy
- Basic knowledge of event-driven systems and distributed computing for stateful systems
- Experience managing and developing high performing individuals
- Experience working with model governance bodies or awareness of the issues facing governance of machine learning models in production
- Experience in requirements management, business analysis or consulting environment
Equal Opportunities
Here at Featurespace we are committed to being a place of equality, inclusion and respect to provide a safe environment for you to bring your authentic self to work. We know that we gain as much strength from our differences as we do our similarities. We value diversity and are dedicated to listening and learning from each other to build and maintain a positive and productive culture. We appreciate this will be an ever-evolving focus for the business to ensure everyone feels supported and has a sense of belonging.
