Our clients are a FTSE100 company structured as a Real Estate Investment Trust. Places People Prefer is at the heart of what they do, they create outstanding places that make a positive difference to people’s everyday lives.
The company invests significantly in understanding its customers and has created a centralised Insight department to serve the needs of the Retail, Office and Residential teams. The team ceates insights from research and data to:
- Be customer oriented, innovating to understand the needs of all their stakeholders
- Strengthen decision-making, supplementing and challenging their current approach
- Generate incremental value, for our customers and shareholders
Key stakeholders for the Insight team include; Asset Management, Leasing, Development, Investor Relations, Strategy and Centre / Campus Management.
The Data Scientist will have access to a significant wealth of data. Working within the Insight team, collaborating with the Data & Analytics technology team, they will be able to leverage the enterprise-wide analytics and storage infrastructure to generate insights that inform decision-making.
- The Insight and Data & Analytics teams are in the midst of implementing a transformational technology driven change programme called the “Insight Capability Programme” or ICP for short – the current phase is focused on completing the delivery of new footfall systems and an in-house sales data collection programme at their retail centres and office campuses due for completion during Summer 2019.
- Data from various internal and external sources including footfall, sales, weather, WiFI, weather, car park systems are plugged into the big data storage infrastructure (AWS, Hadoop and SQL Server) and the Insight Data Scientist will interrogate the data, primarily using Alteryx, and develop insightful reports in Tableau or Power BI.
- Supporting the Business Insight & Analytics Manager, the Data Scientist will act as the Insight team’s data science and analytics expert, working alongside the Data & Analytics technology team to ingest data into the data environment and create reports and bespoke analytics.
- Select appropriate techniques for analysing different types of data
- Extract full value from the existing data sets (footfall, sales, weather, WiFI, weather, car park systems) they have to take superior commercial decisions and provide better service to the occupiers
- Combine data sets together with one another and new data sets (weather, transport/traffic, financial systems, property systems) using the pre-existing data environment and apply advanced analytical techniques to generate new actionable insights.
- Build descriptive and prescriptive models to enable our client to take superior decisions about how they deploy the financial resources on the assets (e.g. further investment, development or disposals), how they operate their assets efficiently day-to-day, how they lease space, to whom they lease space and at what price.
- Conduct analysis and document work in line with our client standards
- Effectively communicate findings, and how these can be used for commercial benefit, to non-technical decisions makers
- Utilise outputs to create compelling story-based presentations and reports for senior management
- Fix and enhance any current dashboards
- Identify data sources to help generate actionable insights for Offices, Storey and Retail to drive income or faster decisions
- Support end-users of dashboards to ensure they can self-serve where approariate
- Seek out feedback, capture requirements and work with the Data & Analytics team to respond to changes requested
- Masters or Doctorate in Statistic, Computer Science or Mathematic disciplines
- Strong academic understanding and practical application of a range of statistical/machine learning techniques, including supervised and unsupervised techniques, such as Regression (e.g. linear, logistic), Factor analysis, Cluster analysis (e.g. K-means), Decision trees (e.g. Gradient-boosted, Random Forest) and Bayesian Probability.
- Clear understanding of when to use different techniques, pros and cons of each, how they work (statistically and computationally), and common pitfalls to avoid. This knowledge will be based on both academic foundations and first-hand experience.
- Ability to handle, cleanse and process large data structured and unstructured sets
- Experienced user of statistical, analytical and visualisation tools, such as Alteryx and Tableau, including creating complex workflows and visualisations from scratch
- Able to code more complex analysis using plug-ins in languages such as SQL, Python and R
- Experience in geo-spatial analytics
- Used to working in both waterfall and agile environments
- Experience in creating and applying both descriptive and predictive models in a corporate environment with clear commercial benefits/outcomes
- Analytical & detail oriented
- Able to see the big picture
- Commercial & customer awareness
- Strong business acumen
- Service ethic
- Effective Communicator & relationship-builder
- Collaborative working style, with low ego
- Team player with an ability to work on their own
- Self-motivated / Proactive
- High professional integrity
For further information please contact Louisa -
020 3574 4125