3 дня назад
Data Analyst
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Analyst (SQL/Python): Developing analytics products, metrics, dashboards, and data pipelines for content acquisition products with an accent on quantitative analysis, data visualization, and analytics engineering. Focus on designing business metrics, maintaining ETL and data modelling capabilities, and uncovering trends and opportunities through cross-functional research.
Location: Lisbon, Portugal or London, United Kingdom
Company
is a research publisher providing journals, books, and technology-enabled products, platforms, and services for researchers, healthcare professionals, and educators.
What you will do
- Analyze the global scientific landscape, publishing business, and content acquisition processes.
- Apply quantitative methods and data storytelling to support product and business decisions.
- Design and deploy key business metrics.
- Create and maintain analytics products, dashboards, and self-service data-querying capabilities.
- Partner with Technology, Business, and User Research functions on deep-dive projects to identify trends, opportunities, and threats.
- Promote data literacy and a data-driven mindset across the organization.
Requirements
- University degree in Mathematics, Statistics, Data Science, Engineering, or another quantitative STEM discipline.
- Previous experience as a Data Analyst or in a similar quantitative role delivering data solutions for product or business problems.
- Advanced SQL and Python skills, including data preparation, manipulation, and analysis.
- Experience with data visualization concepts and tools such as Looker and Plotly.
- Experience with cloud data warehouses such as Google BigQuery and with analytics engineering, including ETL processes, analytics pipelines, data modelling, and data testing.
- Good command of English is required, along with strong collaboration and communication skills.
Nice to have
- Statistical knowledge covering descriptive and inferential statistics and sampling methods.
- Understanding of machine learning techniques.
- Experience turning raw data into clear stories for technical and non-technical audiences.
- Curiosity, attention to detail, quality focus, and strong interpersonal skills.
Culture & Benefits
- Collaborative, multidisciplinary delivery teams.
- Friendly and inclusive working culture.
- Support for personal and professional development.
- Work focused on digital products and services used by researchers, scientists, and students worldwide.
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