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Data Analyst

Made Tech
Bristol, GBR
Full-time
Mid
Hybrid
GBP 37000-45000 yearly / year
Discovered 1 months ago
Power BITableauQuicksightMatplotlibSeabornETL tools

Full Job Posting

Key Responsibilities

  • Apply statistical, qualitative, and data mining techniques tailored to research contexts.
  • Synthesize data to deliver actionable insights and articulate impacts on decision-making.
  • Engage effectively with skeptical colleagues to build consensus and buy-in.
  • Maintain data accuracy, accessibility, and storage using common data sources.
  • Adhere to team data governance, security, and ethical standards.
  • Support continuous improvement, documentation, and process automation (desirable).
  • Utilize and learn data management tools to maintain integration and efficiency.
  • Design conceptual, logical, and physical data models using best practices.
  • Perform data cleansing and standardization to resolve quality issues.
  • Gain exposure to ETL tools to ensure data interoperability across datasets.
  • Collaborate with data professionals to refine modeling and integration practices.
  • Create visually appealing representations tailored to audience requirements.
  • Apply visualization tools (e.g. Tableau, Power BI, Matplotlib, Seaborn).
  • Follow core design and accessibility principles to produce clear, accurate visuals.
  • Incorporate peer feedback to refine visualization quality.
  • Conduct data profiling, validation checks, and multi-source data linkage.
  • Prepare datasets by managing missing values, duplicates, and advanced cleansing.
  • Communicate data limitations to assist stakeholders in informed decision-making.
  • Participate in peer reviews to uphold data accuracy standards.
  • Execute statistical techniques including hypothesis testing, regression analysis, and clustering.
  • Analyze data via programming languages/software to share insights with technical and non-technical audiences.
  • Explore and apply emerging statistical methodologies to real-world problems.
  • Manage expectations and interact across technical and business stakeholder groups.
  • Maintain active updates, respond to inquiries, and foster collaborative environments.
  • Translate basic business requirements into technical solutions.
  • Simplify complex data insights into clear presentations for various audiences.
  • Break down problems logically and generate structured solutions.
  • Make informed decisions, prioritize tasks, and resolve issues efficiently.
  • Demonstrate adaptability, curiosity, and a strong continuous learning orientation.

Skills, Knowledge & Expertise

  • Proficiency in applying various analytical methods such as statistical analysis, data mining, and qualitative analysis.
  • Experience in synthesising research data to present actionable insights and solutions.
  • Ability to articulate the impact of their analysis on decision-making and problem-solving.
  • Effective communication skills to engage and gain buy-in from sceptical colleagues.
  • Familiarity with common data sources and general knowledge of data organisation and storage practices.
  • Understanding of data governance standards and a commitment to following data quality practices set by the team.
  • Ability to contribute to improvements in data management practices by supporting documentation, learning from team training, and actively participating in discussions
  • Experience with using data management tools, with a willingness to learn more about maintaining efficiency and integration.
  • Basic understanding of data governance policies, with a focus on following data security and ethical standards.
  • An interest in learning how to automate data management activities to streamline processes and improve accuracy (desirable).
  • Experience with conceptual, logical, and physical data modelling. Ability to adhere to data modelling standards and best practices.
  • Experience in resolving data quality issues and ensuring data accuracy through cleansing and standardisation techniques.
  • Basic experience with ETL tools for data integration and storage, with a focus on learning how to ensure data interoperability with other datasets.
  • Some experience working with other data professionals, with a focus on learning and improving data modelling and integration practices through teamwork.
  • antiracist-activists
  • disability
  • lgbtqiaplus-allies-and-activists
  • neurodiversity
  • parents-carers
  • Womxn-in-tech

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