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The Data Systems department are looking to place a dynamic and creative individual who can make a strong contribution to our team and systems. Research and develop detailed analysis techniques to utilise the data sources and combine the data to find relationships using state of the art methods and lead deployment of future analytic methods. Enthusiastic, confident, willing to learn, collaborative & energetic.
The key responsibility will be to own and report on Burberry Clients KPIs (sales, productivity, retention, client portfolio growth), track them against client KPIs to drive performance and ensure Sales Associates deliver the yearly targets and remain best in class among their sales peers. Involved in a wide range of ad hoc exploratory analysis to develop a deep understanding on top client profiles and purchase behaviours as part of the wider suite of analytical tools Work with the CRM Manager and Senior Business Analyst to understand business needs and translate them into back-end and front-end development. Ability to understand and interpret data and communicate it in a concise and relevant way to various stakeholders. Regular, effective, timely reporting and analysis.
o Operational Efficiency: Design and implement efficient data operations workflows, including data collection, ingestion, cleaning, and transformation processes backed up by rigorous and relevant SLAs and KPIs o Data Quality Assurance: Develop and enforce data quality standards and controls. o Product Strategy Development and communication: Communicate the vision and strategy for data products and their development and availability on the Data Platform to internal clients within Investments.
Our placement students will also have the opportunity to familiarize themselves with developing tools to improve the live operational activities and the post-event analysis & checks; design and develop GUI supporting live & replay operational tasks. Engage in the continual assessment and review of systems and operations, making proposals for improvement. Ability to demonstrate practical applications and utilization of data analytic work / mathematical and/or statistical reduction on datasets Development of bespoke data analytical and visualization tools Excellent knowledge and skills in machine learning and computer vision Good working knowledge of IT, Networking, communications, software systems etc.
Sub sectors / disciplines: Data Analyst, Business Intelligence Analyst, Financial Analyst, Marketing Analyst
Data analysis is central to informed decision-making. Professionals in this field utilise their analytical skills to interpret data, identify trends, and deliver valuable insights. As a Data Analyst, you will collect, process, and analyse data to extract significant insights that guide crucial business decisions.
Roles encompass Business Analyst, Marketing and Financial Analyst. Precision, statistical expertise, and data visualisation skills are crucial. Data Analysts excel in industries ranging from finance to healthcare, technology, and more, fuelling innovation and efficiency. Whether revealing consumer trends or enhancing operations, a career in data analysis offers ongoing development and impact in the data-driven world.
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Sub sectors / disciplines: Database Administrator, Data Architect, Data Engineer
Roles within the Big Data sector are deemed the driving force of today's digital era, fuelling decisions and innovations with extensive information streams. Within this broad domain, Data Engineers work meticulously to ensure data flows efficiently and is processed accurately. Accompanying them, Data Architects design the blueprints, crafting the frameworks for data storage and integration. Further in-depth, Database Administrators act as gatekeepers, safeguarding data's integrity while managing and securing vast databases. On the infrastructure front, Data Centre Operators maintain the essential systems, ensuring optimal uptime and resilience.
For those captivated by the complexities of data and its transformative capacity, the big data sector presents a landscape brimming with opportunities for advancement, innovation, and the chance to contribute significantly to the digital revolution.
Sub sectors / disciplines: Data Scientist, Machine Learning Engineer, Statistician
The Data Science job sector is a pivotal element of modern technological progress, transforming vast data streams into actionable insights and pioneering solutions. Within this vibrant field, Data Scientists spearhead efforts, navigating through complex datasets to detect patterns and forecast outcomes. In a more specialised area, Machine Learning Engineers utilise algorithms and models to enable machines to learn from and respond to data. Statisticians, with their sharp understanding of numbers, form the robust backbone of the sector, testing hypotheses and ensuring data accuracy. Additional roles, such as Data Visualisation Specialists, facilitate the translation of raw data into forms easily understood by humans, while Deep Learning Specialists extend the limits of machine perception and comprehension.
For those drawn to numbers, algorithms, and the narratives data can unfold, the Data Science sector offers a realm of limitless possibilities, challenges, and the prospect of driving future innovations.
Sub sectors / disciplines: Administrators, Support, Other, Data Entry
Admin, support, and data entry jobs constitute the operational core of many organisations. Admin roles manage crucial tasks, from organising schedules to enabling communications. Support positions aid various departments, promoting a unified working environment. Meanwhile, data entry professionals concentrate on accurately recording and updating information, ensuring records are timely and exact.
Collectively, these roles facilitate seamless business operations, combining meticulous attention to detail with vital logistical support, fostering an efficient and harmonised work ecosystem.