Senior Data Analyst

Overview

Senior Data Analyst at Made Tech, supporting public sector organisations to become data-led.

The role is hands-on and focuses on data analysis, modelling, predictive analytics, and data visualisation to deliver customised client solutions.

The role includes mentoring and leading data-focused projects, collaborating with clients, and promoting data governance and best practices.

Responsibilities

• Data analysis and reporting: conduct in-depth data analysis, generate reports, and provide actionable insights for client projects.
• Data and BI visualisation: produce BI dashboards using industry-standard tools (Power BI, Tableau, Quick Sight, etc.).
• Client interaction: collaborate with clients to understand needs, translate them into analytical solutions, and present findings clearly and actionably.
• Mentoring and leadership: mentor junior analysts, lead data-focused projects, and set best practices in data analysis.
• Application of analytical techniques: apply statistical analysis, data mining, and qualitative analysis; select techniques based on context and data.
• Synthesis of research data: synthesise research data to present actionable insights and articulate impact on decision-making.
• Engagement with sceptical colleagues: communicate effectively to gain buy-in and foster collaboration while upholding data practices.
• Advisory and critique: advise on analytical techniques and critique colleagues' findings to maintain high standards.
• Understanding of data sources and storage: knowledge of data sources, organisation, and storage practices, maintaining data integrity and accessibility.
• Advocacy for data governance: advocate for data governance standards and influence team adherence to data quality practices.
• Continuous improvement: implement continuous improvements in data management through documentation, training, and team engagement.
• Toolset management: define and support common toolsets for data management and ensure seamless integration.
• Automation of data management: automate data management activities to streamline processes and increase accuracy.
• Compliance with data governance policies: understand and ensure compliance with data governance policies, maintaining data security and ethics.
• Data modelling: proficient in conceptual, logical, and physical modelling with adherence to standards and best practices.
• Data cleansing and standardisation: resolve data quality issues and ensure accuracy through cleansing and standardisation techniques.
• Data integration tools: proficient with ETL tools for data integration and storage; ensure interoperability with other datasets.
• Collaboration with data professionals: work with other data professionals to improve modelling and integration standards.
• Interpretation of requirements: interpret data visualisation requirements and create meaningful representations for diverse audiences.
• Proficiency in visualisation tools: experience with Tableau, Power BI, and Python libraries like Matplotlib and Seaborn; select appropriate visualisation types.
• Application of visualisation standards: apply design principles for clear, accurate, accessible visualisations with accessibility considerations.
• Mentorship in visualisation: review and advise juniors to improve quality and efficiency of data visualisations.
• Data quality assurance: implement data quality assessment processes including profiling, cleansing, and standardisation.
• Data validation and linkage: perform data validation checks and integrate data from various sources for consistency and accuracy.
• Data cleansing and preparation: define cleansing processes and prepare data for analysis by handling missing values, outliers, and duplicates.
• Communication of data limitations: articulate data constraints to stakeholders to provide context for decision-making.
• Peer review and quality control: conduct peer reviews to validate data outputs and ensure accuracy and reliability.
• Knowledge of statistical methodologies: proficient in methods such as hypothesis testing, regression, clustering, and time series; select techniques based on project requirements.
• Data analysis and interpretation: use statistical software or programming languages to analyse data and generate insights; communicate findings to technical and non-technical stakeholders.
• Application of emerging theory: willingness to explore and apply new statistical methodologies to solve problems and adapt to evolving theories.
• Business Skills
• Stakeholder communication: engage with a diverse range of stakeholders; manage expectations and facilitate productive discussions.
• Active and reactive communication: handle proactive updates and reactive inquiries to maintain collaboration.
• Interpretation of stakeholder needs: translate stakeholder requirements into technical solutions and bridge gaps between technical and non-technical stakeholders.
• Presentation of insights: present complex data clearly to diverse audiences, including senior management.
• Problem-solving: apply logical and creative thinking to resolve complex problems and generate solutions.
• Decision-making and action-taking: make informed decisions, prioritise tasks, and take appropriate actions.
• Adaptability and continuous learning: demonstrate adaptability and a commitment to ongoing learning.
• Eligibility

Life at Made Tech notes that an increasing number of customers require security clearances.

Successful candidates should have eligibility for SC (security check).

Eligibility for SC requires 5 years UK residency and 5 years of employment history (or back to full-time education).

If eligibility is not evident during the interview process, we will inform you why.

About Made Tech

Made Tech is on a mission to use technology to improve society for everyone.

We help organisations transform, deliver and manage digital products and services.

Our work includes projects such as the Homes for Ukraine service delivered in 2 weeks, facilitating housing repairs online for local authorities, digitalising NHS service access, and initiatives to drive environmental improvements through real-time asset monitoring.

We were named a finalist in the Raising the Bar for Workplace Transparency Award in the Shift People Awards and maintain an open-access employee handbook launched five years ago.

We are committed to building a happy, inclusive and diverse workforce.

Benefits

• 30 days paid annual leave
• Flexible parental leave options
• Remote working options
• Paid counselling, plus financial and legal advisory services
• Flexible benefits platform including a Smart Tech scheme, Cycle to work scheme, and an individual benefits allowance (can be used for health care, pension, etc.)
• Social and wellbeing calendar of events for all employees
• #J-18808-Ljbffr