Data Scientist - Hire or get hired
Your complete guide to the Data Scientist Role: Duties, salary & hiring tips
Purpose of the Data Scientist
The Data Scientist uses advanced analytics, statistical models, and machine learning techniques to uncover insights, solve complex problems, and drive strategic decision-making.
Data Scientist's duties and responsibilities
• Data Analysis:
Extract, clean, and analyse large datasets.
• Modelling:
Build predictive models using machine learning algorithms.
• Visualisation:
Create dashboards and reports to communicate findings.
• Collaboration:
Work with business units to identify data-driven opportunities.
• Innovation:
Research and apply new analytical techniques and tools.
Extract, clean, and analyse large datasets.
• Modelling:
Build predictive models using machine learning algorithms.
• Visualisation:
Create dashboards and reports to communicate findings.
• Collaboration:
Work with business units to identify data-driven opportunities.
• Innovation:
Research and apply new analytical techniques and tools.
Requirements and qualifications for a Data Scientist
• 3–7 years’ experience in data science or analytics
• Proficiency in Python, R, SQL, and machine learning libraries
• Strong knowledge of statistical methods and data modelling
• Experience with BI tools like Tableau or Power BI
• Degree in data science, statistics, or related field
• Proficiency in Python, R, SQL, and machine learning libraries
• Strong knowledge of statistical methods and data modelling
• Experience with BI tools like Tableau or Power BI
• Degree in data science, statistics, or related field
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AI continues to reshape workforce priorities, with 47% of businesses seeking candidates with at least a base-level understanding of AI. Key skills growing in importance include automation and IT process orchestration (63%), continuous learning in AI (45%), and cybersecurity using AI-driven threat detection (37%). Cybersecurity, upskilling, and AI and machine learning are now the top three business priorities, each cited by over 50% of companies.
Contractor usage has remained relatively stable, with 81% of companies expecting no change in 2025, and nearly half keeping contractor levels under 10%. The shift towards AI, automation, and cybersecurity signals an evolving skills landscape, requiring businesses to balance permanent hires with specialised expertise to stay competitive.
