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Springer Nature

Data Analyst

Posted 3 Days Ago
In-Office
London, Greater London, England, GBR
Entry level
In-Office
London, Greater London, England, GBR
Entry level
Analyze publishing and content acquisition data to support digital product decisions. Design business metrics, build analytics products and dashboards, conduct quantitative research, maintain ETL pipelines and data models, and communicate insights to technical and non-technical stakeholders. The role also promotes data literacy and data-driven decision-making across the organization.
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Job Title: Data Analyst 

Location(s): Lisbon, Portugal & London, United Kingdom 

Application Deadline: (if applicable)    

  

About Springer Nature (will be included on all adverts)  

Springer Nature is one of the leading publishers of research in the world. We publish the largest number of journals and books and are a pioneer in open research. Through our leading brands, trusted for more than 180 years, we provide technology-enabled products, platforms and services that help researchers to uncover new ideas and share their discoveries, health professionals to stay at the forefront of medical science, and educators to advance learning. We are proud to be part of progress, working together with the communities we serve to share knowledge and bring greater understanding to the world. For more information, please visit about.springernature.com and follow @SpringerNature. 

 

At Springer Nature, we recognise that great talent develops through many different paths. We encourage applications from individuals with strong transferable skills, provided they are supported by relevant experience that shows how those skills have been successfully applied in practice. Our hiring approach balances skills, experience, and potential to ensure each role is fulfilled with both short term effectiveness and long term growth in mind.   

 

About the Role  

As a data analyst in the Content Acquisition Product Group, you will connect with Technology, Business and User Research functions, using your skills in data analysis and quantitative research to deliver value across the organization. You will support the development of digital products through their lifecycle – from planning and analysis to delivery and operations – while considering customer, business and wider scientific landscape perspectives.   

 

Role Responsibilities 

  • Understanding the global scientific landscape, our publishing business and its content acquisition processes through data.  
  • Applying business knowledge, quantitative methods and proficient storytelling to help teams keep data at the core of their thinking and decision-making.  
  • Designing and deploying key metrics to measure different aspects of the business.  
  • Creating and maintaining analytics products for easier data querying and self-service.  
  • Creating and maintaining dashboards to track metrics and visualize insights.  
  • Partnering with cross-functional teams for deep dive research projects to uncover trends, opportunities and threats at longer timescales.  
  • Help drive the shift to a data mindset as part of our culture – promoting data literacy across the company, while advocating and educating teams to keep data front and center. 

 

Experience, Skills & Qualifications:  

Essential  

  • University degree in a quantitative discipline (e.g., Mathematics, Statistics, Data Science, Engineering or related STEM fields).  
  • Previous experience as a Data Analyst or similar quantitative roles, creating impactful data solutions for solving product/business problems.  
  • Strong analysis design, implementation and ownership skills.   
  • Excellent data preparation and manipulation skills - Advanced proficiency in SQL and advanced analysis experience in Python.   
  • Experience in data visualization concepts and tools (BI – e.g. Looker and Python-based – e.g. Plotly).  
  • Experience using cloud-based data warehouses (e.g. GCP BigQuery or similar).  
  • Experience in analytics engineering – Creating, owning and maintaining ETL processes, setting up analytics pipelines, data modelling and data testing capabilities (e.g. dbt, Dataform). 

 

Desirable   

  • Solid statistical knowledge (e.g. descriptive statistics, inferential statistics, sampling methods etc.). Understanding of machine learning techniques is a plus, but not mandatory.  
  • Amazing data storyteller – Turns raw data into meaningful stories that effectively engage technical and non-technical audiences.  
  • Intellectually curious, motivated, detail-oriented and quality-focused: constantly looking for better questions, hypothesis, explanations.  
  • Strong collaboration, communication, and interpersonal skills. 

 

At Springer Nature, our mission is to be part of progress – and that begins with inclusion: of people, perspectives, and ideas. We believe that diverse perspectives drive progress, and we are committed to creating an environment where people and ideas can flourish. If you have any access needs related to disability, neurodivergence or a chronic condition, please contact us so we can make all necessary accommodations.


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Springer Nature London, England Office

4 Crinan Street London, London, United Kingdom, N1 9XW

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