Data Analyst & Visualization Specialist

Job Description

Requirements

• - Bachelor’s degree in Data Science, Statistics, Computer Science, or a related field.
• - 5+ years of experience in data analysis and visualization.
• - Proficiency in data visualization tools such as Tableau, Power BI, or equivalent.
• - Strong skills in SQL for data querying and manipulation.
• - Experience with statistical analysis and data modeling techniques.
• - Ability to translate complex data into understandable insights through visual storytelling.
• - Excellent problem-solving and critical thinking abilities.
• - Strong communication and collaboration skills.
• - Attention to detail and a passion for data accuracy.
• - Required Skills & Technologies
• - - SQL — advanced analytical queries, window functions, aggregations, cross-source joins
• - - Data visualization — strong opinions on when to use charts vs. tables vs. narrative; experience with Recharts, D3, Tableau, Power BI, or Looker
• - - Figma — wireframing and prototyping reporting surfaces
• - - React + TypeScript — ability to build or modify dashboard components (working alongside the Full Stack Engineer, not replacing them)
• - - Python — data analysis, pandas, scripting for ad hoc analysis
• - - Understanding of dimensional models and how to query a warehouse
• - - Excel / Google Sheets — quick-turn analysis and ad hoc reporting
• - - Business intelligence concepts: KPIs, OKRs, trend analysis, variance reporting, cohort

Responsibilities

• - Collect, analyze, and interpret large datasets to identify trends and patterns.
• - Develop clear and insightful visualizations and dashboards using tools such as Tableau, Power BI, or similar.
• - Collaborate with stakeholders to gather requirements and deliver relevant data solutions.
• - Perform data cleansing and ensure data quality.
• - Generate regular and ad-hoc reports to support business initiatives.
• - Communicate findings and insights effectively to both technical and non-technical audiences.
• - Stay current with data analysis and visualization best practices and tools.
• - Executive reporting: recurring KPI reports, programme status summaries, budget variance analysis, milestone tracking
• - Data analysis: identifying trends, anomalies, and insights across operational data (finance, HR, procurement, research portfolio)
• - Visualization design: defining the right chart, metric, or narrative for each audience — working with the Full Stack Engineer to implement dashboard views
• - Figma mockups for new reporting surfaces — wireframes and visual specs before engineering build
• - Ad hoc analysis: answering leadership questions that require digging into data ("why did procurement spend spike in Q3?")
• - KPI definition support: working with business owners to define meaningful, measurable KPIs
• - Reporting cadence: automated or semi-automated generation of recurring status reports and summaries

Skills Required