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Data Scientist
Отличная позиция в стабильной, но быстрорастущей компании с четким фокусом на современные технологии (GCP, GenAI). Хороший социальный пакет, включая бюджет на обучение и гибридный график в Лондоне.
Сложность вакансии
Роль требует не только сильных технических навыков в ML и Python, но и развитого «продуктового мышления». Кандидату необходимо уметь самостоятельно доводить модели до продакшена и эффективно общаться с бизнес-стейкхолдерами.
Анализ зарплаты
Зарплата в объявлении не указана, но для позиции Data Scientist в Лондоне рыночный диапазон составляет от £55,000 до £85,000 в зависимости от опыта. Предлагаемый соцпакет (пенсия 7%, бюджет на обучение) соответствует стандартам топовых финтех-компаний Великобритании.
Сопроводительное письмо
I am writing to express my interest in the Data Scientist position at Policy Expert. With a strong background in building predictive models and a product-oriented mindset, I am drawn to your mission of leveraging real-time ML engineering to enhance customer experience in the insurance sector. My experience in translating complex business problems into technical solutions aligns perfectly with your team's goal of bridging the gap between data science and business outcomes.
In my previous roles, I have focused on the end-to-end development of data products, from initial statistical analysis to collaborating with ML engineers for production deployment. I am particularly excited about the opportunity to work with GCP Vertex AI and explore GenAI applications within your diverse datasets. I am confident that my proactive approach and commitment to writing efficient, optimized Python code will contribute significantly to Policy Expert's ambitious growth plans.
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Описание вакансии
Policy Expert – Data Scientist
🚀Are you ready to transform the insurance industry?
Policy Expert is a forward-thinking business that loves to get things done. Leveraging proprietary technology and smart data, we offer reliable products and a wow customer experience.
Having achieved rapid growth since being founded in 2011, we’ve won over 1.5 million customers in Home, Motor and Pet insurance and have been ranked the UK’s No.1-rated home insurer by Review Centre since 2013. 🏆
Hear from our team about what it's like working at Policy Expert ✨
About our Data Science Team
This is an exciting time for us as we expand our Data Science capabilities to support our ambitious growth plans. We are embarking on a new chapter where we are increasing the use of data science and real-time ML engineering techniques to take our market leading models to the next level. And the customer is at the centre of this ambition. We have a plethora of datasets and cutting-edge technologies that can (and should!) be leveraged to create propositions that customers will rely on and love.
Your day to day:
As a Data Scientist you will be building predictive statistical models, machine learning models and pipelines to drive business growth. You will work with ML Engineers to ensure those are deployed in production and delivering real value. Take ownership of your area and the models you build. This role also plays a key role in acting as the bridge between Data Science and the business and therefore, you must be able to translate business problems into a technical one with clear outcomes. You won’t be on your own though you will have active support from the Lead / Head of Data Science and product owners. Activities will include:
- Developing data science and ML solutions (including GenAI) to drive growth, solve problems and increase automation across the business.
- Work within a cross-functional team (product managers, ML engineers, analysts) to deliver business goals + help define the product roadmap
- Input into priorities using data to quantify new opportunities and discover the art of the possible
- Design and monitor A/B tests showing the impact of initiatives.
- Be an advocate of data science and ML, communicating its value to colleagues across the business.
Who are you:
- Have an end-to-end mindset. Experience in designing and building data products using large datasets along with how they would be deployed in production. Working closely with machine learning engineers to do this would be a plus but not required.
- Ability to apply knowledge in statistics and machine learning to real world problems which has had quantitative impact on the business
- Self-starter showing proactiveness to unblock yourself when blockers do occur
- Have a product mindset over and academic one. Think “How will this model or my work impact the business?”
- MLOps experience is not required but would be beneficial to have an understanding at least at a theoretical level
- Nice to have experience with creating solutions using GenAI
- A desire to interact with stakeholders and translating business problems into practical solutions
- Good team working and communication skills with ability to explain complex techniques to non-technical audience.
- Good knowledge of data science tools and techniques, which you can use to solve problems creatively and to create opportunities for the business.
- Good programming skills with Python and good working knowledge of SQL and experience querying large datasets.
- A passion for building data products that can change a business at the fundamental level
- Able to work with Data Engineers to identify the data engineering requirements for a data science product.
- Understand the need to cleanse and prepare data before including it in data science products
- Familiarity with Python best coding practices and how to write efficient, optimised code.
- Knowledge of the insurance industry would be an advantage but not essential.
- Ideally you will have experience working with the GCP vertex AI, or similar services.
Benefits:
📍 This role will be based in our London office in a 50/50 Hybrid mode.
💸 We match your pension contributions up to 7%
🏥 Private medical & Dental cover
📚 Learning budget of £1,000 a year + Study leave (with encouragement to use it)
😁 Enhanced maternity & paternity
🚉 Travel season ticket loan
🎟️ Access to a wide selection of London O2 events and use of a Private Lounge
🌈 Employee Wellbeing Programme
🚪 Prayer room in Office
What We Stand for and Next Steps
“We pride ourselves on being an equal opportunity employer. We treat all applications equally and recruit based solely on an individual’s skills, knowledge, and experience. The quality and growing diversity of our team is a testament to this commitment”
At Policy Expert, we are committed to fostering an inclusive and supportive environment for all candidates. If you require any reasonable adjustments during the interview process to accommodate your needs, please do not hesitate to let us know. We are dedicated to ensuring every candidate has an equal opportunity to succeed and will work with you to provide the necessary support.
We aim to be in touch within 14 working days of receiving your application – you will be notified if your application is successful or unsuccessful. Please be encouraged to apply even if you do not meet all the requirements.
Useful links:
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Навыки
- A/B Testing
- Python
- Machine Learning
- SQL
- Statistics
- Data Engineering
- MLOps
- Google Cloud Platform
- Generative AI
- Vertex AI
Возможные вопросы на собеседовании
Вакансия подчеркивает важность продуктового подхода над академическим.
Расскажите о случае, когда вам пришлось упростить модель или изменить подход, чтобы быстрее принести пользу бизнесу. Как вы оценивали этот компромисс?
Компания использует GCP Vertex AI и стремится к внедрению ML в реальном времени.
Каков ваш опыт работы с облачными ML-платформами (например, Vertex AI) и как вы подходите к обеспечению масштабируемости ваших моделей в продакшене?
Упоминается необходимость работы с большими данными и SQL.
Опишите ваш самый сложный проект по обработке данных. С какими проблемами качества или объема данных вы столкнулись и как их решили?
В описании указано использование A/B тестирования для оценки влияния инициатив.
Как вы проектируете A/B тесты для ML-моделей и какие метрики, помимо точности модели, вы считаете наиболее важными для страхового бизнеса?
Компания заинтересована в применении генеративного ИИ.
Есть ли у вас идеи или опыт применения GenAI в контексте страхования (Home, Motor, Pet) для улучшения клиентского опыта или автоматизации?
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