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Data Scientist- Social Impact

YunoJuno
Glasgow
3 weeks ago
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The TVC Analyst will play a crucial role in transforming complex data sets into actionable insights, contributing to projects that have a social impact. The role involves addressing stakeholder requests and developing a robust data analysis infrastructure.


Key responsibilities:

• Impact Analysis: Design and execute in-depth analyses to measure the impact of various projects in to-be-determined efforts.

• Insight Communication: Translate complex data findings into clear, visually compelling reports and dashboards customised for a diverse set of collaborators.

• Ad Hoc Analysis: Provide prompt and accurate responses to data-driven queries from various collaborators.

• Collaboration: Work closely with teams to identify data needs and support project objectives through impactful insights.

• Data Infrastructure Development: Develop and maintain data pipelines for clean, organised, and accessible data.


Role requirements:

• Programming Proficiency: Mastery in data analysis tools such as SQL and Python.

• Statistical Expertise: Understanding of statistical techniques like hypothesis testing, regression modelling, and experimental design.

• Data Storytelling: Translate technical findings into understandable narratives and visuals for a non-technical audience.

• Problem-Solving: Analytical mindset to identify trends and anomalies.

• Communication & Collaboration: Excellent verbal and written communication skills with a knack for team collaboration.

• Delivery Focused: Action-oriented with initiative for exceptional outcomes.

• Project Management Skills: Capable of independent execution and leading projects end-to-end.

• AI-first: Utilise AI tools to boost productivity.


Additionally advantageous:

• Experience in Impact Measurement: Previous work in evaluating impacts within sectors such as science, sustainability, or education.

• Domain Knowledge: Familiarity with sustainability metrics, life sciences data, or educational assessment techniques.

• Collaborative Software Development: Understanding of version control systems like Git.

• Data Science Foundations: Insight into machine learning principles and techniques for advanced analysis.

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