Data Science Jobs in London

London is a thriving hub for data science professionals, offering a vast array of opportunities across various industries. The city’s dynamic market demands expertise in machine learning, big data analytics, and statistical analysis, making it an ideal location for data scientists seeking to advance their careers. Companies in finance, healthcare, retail, and technology sectors are actively seeking data scientists to leverage data for strategic decision-making.

1. Teradata

Requirements:

• Expertise in database management and analytics.
• Proficient with cloud analytics and data-sharing services.
• Skills in handling massive and mixed data workloads.

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2. Unified

Requirements:

• Strong analytical skills in data-driven social advertising.
• Experience in optimizing investments across the consumer journey.
• Knowledge of proprietary technology for marketing data analysis.

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3. Alteryx

Requirements:

• Proficient in analytics, data science, and process automation.
• Experience with end-to-end platform management.
• Capable of turning data into actionable insights.

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4. Civis Analytics

Requirements:

• Strong background in data science software and consultancy.
• Ability to create tailored solutions for clients.
• Interdisciplinary team collaboration skills.

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5. Sumo Logic

Requirements:

• Expertise in real-time analytics and cloud-native solutions.
• Skills in log aggregation and security threat analysis.
• Experience with digital businesses and operational issue investigation.

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6. Sisense

Requirements:

• Proficiency in business intelligence software.
• Skills in data modeling, visualization, and connectivity.
• Ability to deliver AI-driven platform solutions.

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7. Algorithmia

Requirements:

• Experience in machine learning model deployment and management.
• Skills in managing production machine learning lifecycle.
• Ability to integrate solutions within operational processes.

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8. Resurface Labs

Requirements:

• Strong skills in API security and management software.
• Experience with real-time data capture and analysis.
• Knowledge of different API architectures.

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9. Cropin

Requirements:

• Expertise in AI-led AgTech and data-driven farming.
• Experience with satellite imagery and pixel-level data analysis.
• Skills in enhancing the ag-ecosystem with data insights.

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10. ScienceSoft

Requirements:

• Experience in CRM, Data Analysis, and Information Security.
• Strong testing and quality assurance capabilities.
• Knowledge of various IT infrastructures and applications.

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11. Appsilon

Requirements:

• Proficiency in data science consulting across various sectors.
• Experience with finance, healthcare, maritime, retail, and real estate.
• Demonstrated quality of services in competitive settings.

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12. Addepto

Requirements:

• Strong background in Machine Learning (ML) and Business Intelligence (BI).
• Experience delivering end-to-end data projects.
• Skills in data warehousing and reporting architecture.

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13. Statworx

Requirements:

• Expertise in data science, ML, and AI consulting.
• Experience with deep learning and predictive analytics.
• Skills in sales forecasting and online conversion rate predictions.

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14. Palantir Technologies

Requirements:

• Proficiency with data integration and analysis platforms.
• Experience solving complex problems in diverse industries.
• Skills in developing scalable data-driven solutions.

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15. Meta (Facebook)

Requirements:

• Strong background in data science with a focus on social media metrics.
• Experience leveraging data to drive business value.
• Ability to present data-driven insights to senior leaders.

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16. Google

Requirements:

• Strong expertise in algorithms, machine learning, and data structures.
• Proficiency in programming languages such as Python or Java.
• Experience with large-scale systems and data analysis.

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17. Amazon

Requirements:

• Experience in building complex data pipelines and machine learning models.
• Proficiency with AWS services related to data processing and analytics.
• Strong problem-solving skills and business acumen.

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18. IBM

Requirements:

• Deep knowledge of artificial intelligence (AI) and cognitive computing.
• Experience with data visualization and data manipulation tools.
• Strong analytical skills with the ability to work across different teams.

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19. Microsoft

Requirements:

• Expertise in cloud computing, especially Azure, and related data services.
• Strong skills in programming and data modeling.
• Ability to work on cross-platform data integration.

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20. Salesforce

Requirements:

• Experience with CRM analytics and customer data platforms.
• Proficiency in SQL and experience with Salesforce tools like Tableau.
• Strong analytical and communication skills.

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21. KPMG

Requirements:

• Strong background in quantitative methods and statistical modeling.
• Experience with data audit, compliance, and governance.
• Excellent communication and consultancy skills.

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22. Deloitte

Requirements:

• Proficiency in handling large datasets and conducting complex data analyses.
• Knowledge of machine learning techniques and predictive modeling.
• Excellent project management and client interaction skills.

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23. EY (Ernst & Young)

Requirements:

• Expertise in data analytics and business intelligence solutions.
• Strong skills in using data analytics to drive business insights and strategies.
• Experience with regulatory and compliance projects.

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24. Accenture

Requirements:

• Experience with AI, machine learning, and data architecture.
• Ability to design and implement scalable data solutions.
• Strong consulting skills and ability to work in a fast-paced environment.

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25. PwC (PricewaterhouseCoopers)

Requirements:

• Strong analytical skills with experience in data mining and statistical analysis.
• Proficiency in visualization tools and techniques.
• Excellent interpersonal and team collaboration skills.

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• Indeed UK
• Glassdoor UK
• LinkedIn Jobs
• DataJobs.com

The salary for data scientists in London can vary widely depending on the company, experience, and the specific role. On average, a data scientist might expect to earn between £45,000 and £70,000 annually. Senior roles can command salaries upwards of £90,000, especially in competitive sectors like finance and tech. Factors influencing salary include expertise in machine learning, big data technologies, and the ability to derive actionable insights from complex datasets.

What qualifications are needed to become a data scientist in London?

Typically, a Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related field is required. Advanced roles may require a Master’s or Ph.D. Additionally, proficiency in programming languages such as Python or R, and tools like SQL and Tableau, is often essential.

How important is industry experience for securing a data science job in London?

Industry experience is highly valuable as it demonstrates the ability to apply theoretical knowledge to real-world data. Employers often look for candidates with experience in specific industries such as finance, healthcare, or retail depending on the sector they operate in.

What are the best ways to find data science job opportunities in London?

Job portals like LinkedIn, Indeed, and Glassdoor are great resources. Networking through industry meetups, conferences, and seminars can also provide valuable contacts and leads. Additionally, directly checking the careers pages of companies you’re interested in is a recommended approach.

What is the typical career progression for a data scientist in London?

Career progression can vary, but typically starts from junior data scientist to senior data scientist, and then to positions such as data science manager or lead data scientist. Some may transition into related roles like data architect or data engineer, or even into managerial roles focusing on analytics strategy.

Are there opportunities for ongoing learning and development in the data science field in London?

Yes, continuous learning is a key part of a career in data science due to the fast-evolving nature of technology and methodologies. Many employers offer training programs, and there are numerous workshops, certifications, and courses available, particularly in London, which can help professionals stay updated with the latest tools and techniques.