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Data Analyst / Scientist or Senior Data Analyst / Scientist \n Bristol or London \n \n About us \n \n Hoare Lea is a human-centric and planet-conscious engineering consultancy. We offer intelligent and sustainable solutions to complex design challenges for the built environment throughout the UK and further afield. \n \n We provide a wide range of engineering and consultancy services, including acoustics, air quality, building services (MEP), fire, lighting, security and sustainability to name but a few. Together, our highly skilled teams use technical expertise and problem-solving skills to bring buildings to life. We ensure that whatever the building, its design is outstanding, and its operations meet the needs of the communities it serves. \n \n We are as committed to providing an environment where everyone can realise their unique potential. So, in joining Hoare Lea, you will experience a business that enriches your knowledge, supports your wellbeing, and welcomes your individuality. You’ll have the opportunity to participate in our 9-day fortnight scheme, thriving community groups, varied social and networking events, and extensive professional and technical development schemes. We also offer an extensive benefits package, including private medical cover, an electric vehicle salary sacrifice scheme, stock options, and 25 days of annual leave (increasing with service), alongside flexible and hybrid working. \n \n Whatever your ambitions or circumstances, our aim is to enable everyone to develop their knowledge, give their best, and enjoy what they do. \n \n About the role \n \n Our multi-disciplinary software, product, and data team serves as a central hub of digital expertise and innovation, supporting projects across the company. We work collaboratively with engineers, consultants and other specialists to use data and technology to solve real-world problems and improve the services we provide to our clients. \n \n We have an opportunity for a Data Analyst/Scientist or Senior Data Analyst/Scientist to play a key role in using data, analytics, statistical methods and data science to generate insight, support decision-making and improve our engineering services. \n \n This is a broad analytical role. You will work across the full lifecycle of a problem: understanding stakeholder needs, exploring and assessing data, identifying appropriate analytical approaches, communicating findings and, where appropriate, developing statistical or machine-learning models or client-ready insights/tools. This is a role for someone who enjoys variety and has a critical eye for finding the right solution for the problem. Sometimes this may be exploratory analysis, a dashboard or a set of clearly defined metrics; in other cases, it may involve forecasting, statistical modelling, machine learning or building/working with AI. \n \n It's an exciting time to join our Digital team. Working alongside a range of specialist engineers and consultants, you will be joining a collaborative, knowledgeable, highly engaged team, and offer a supportive, flexible, and high-performing work culture. In a time where building and energy resilience is ever more important, we are driving forward innovation to make an impact with data and technology. \n \n You will have the opportunity to engage in a variety of high-impact projects, working on challenging problems for some of the UK’s most notable organisations, including the NHS and Oxford University. Our team has recently worked on creating data science-led for managing estates in hospitals, building energy forecasting models, and harnessing data on building performance to create better designed buildings of the future. \n \n In this key and varied role, you can expect to: \n \n\n • Work with engineers, consultants, product teams and other stakeholders to understand their needs and translate sometimes ambiguous questions into well-defined analytical problems.\n, • Develop and implement data-driven solutions to solve real-world business problems across the company.\n, • Use SQL, Python and other analytical tools to investigate datasets, identify trends and relationships, test hypotheses and generate actionable insights.\n, • Apply appropriate statistical techniques, forecasting methods, ML and AI approaches where they add value to the problem being solved.\n, • Collaborate with the product and software engineering teams to turn analytical work into reusable tools, workflows and data-driven products where appropriate.\n, • Develop reproducible and maintainable analytical code, following best practices, including version control, testing, and peer reviews.\n, • Contribute to the development of analytical and data science capability across the business by sharing approaches, reusable methods and good practice\n\n \n About you \n \n To be successful in this role you’ll need: \n \n Essential skills: \n \n\n • Experience applying data and analysis to real-world business, engineering or operational problems.\n, • Strong analytical problem-solving skills, with the ability to take an initially ambiguous question and determine an appropriate analytical approach.\n, • Ability to work on projects independently and own deliverables.\n, • Strong proficiency in Python for data manipulation, analysis, visualisation and data science (e.g., Pandas, NumPy, Scikit-learn).\n, • Proficiency in data querying languages (e.g., SQL). Solid understanding of software engineering best practices (version control, unit testing, code review, etc.).\n, • Strong experience with data visualisation frameworks (e.g., PowerBI, Streamlit).\n, • Experience applying machine learning and AI, including generative AI, to real-world problems where it provides clear benefit.\n, • Familiarity with statistical concepts and their application in data analysis.\n, • Solid communication skills, capable of effectively engaging with and presenting findings to both technical and non-technical audiences.\n, • Understanding of data governance, privacy, responsible AI and other relevant standards.\n\n \n Desirable skills: \n \n\n • Knowledge of the engineering industry and its challenges.\n, • Experience with one of the major machine learning frameworks (TensorFlow or PyTorch).\n, • Knowledge of mathematical optimisation methods, such as linear, integer or constraint optimisation, and associated tools (e.g. OR-Tools).\n, • Experience with MS Fabric or equivalent data warehousing solution.\n, • Experience working in a cloud computing environment.\n, • Familiarity with containerisation and deployment technologies (e.g., Docker, CI/CD pipelines).\n\n \n For candidates joining at Senior level, we would additionally expect you to lead more complex or ambiguous analytical projects, shape analytical approaches and overarching priorities, work independently with senior stakeholders, review and support the work of others, and help raise analytical standards across the team. \n \n How to apply \n \n To apply simply complete a CV profile and submit your application. \n \n If shortlisted, one of our recruitment team will be in touch to arrange an introductory call (about 30 minutes) to discuss the role and your experience in more detail. From there, successful candidates will be invited to attend a panel interview, either via Microsoft Teams or in person at one of our offices. We aim to provide feedback at each stage of the process. \n \n Adjustments and accommodations \n \n If there are adjustments or accommodations that we can put in place to help you participate and give your best at any stage of the recruitment process (whether relating to disability, neurodivergence or anything else) please let us know. \n \n Data privacy \n \n We have updated our terms and conditions for candidates, click here to find out more. \n \n Recruitment agencies \n \n We have a Preferred Supplier List of trusted partners who assist us when required. We do not acknowledge speculative CVs or unsolicited candidate introductions from agencies not on the list. \n

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