A template for analysts who turn raw data into business decisions.
Data analysts turn raw business data into insights that help teams make better decisions. A typical week includes writing SQL queries, building dashboards in Tableau or Power BI, running ad hoc analyses for stakeholders, and presenting findings to non-technical managers. They work in finance, retail, healthcare, marketing, logistics — any sector that collects data, which is all of them. Most data analysts report to a Head of Data, Analytics Manager, or sometimes directly to a business unit lead like the Head of Marketing or Finance Director.
Data Analyst with 3 years of experience transforming complex datasets into actionable business intelligence. Proficient in Python, SQL, and Tableau with a background in statistical modelling and A/B testing.
Data Analyst CVs must show that you can extract insights that matter. Recruiters want to see specific tools (Python, SQL, Tableau), the types of analysis you have performed (forecasting, A/B testing, cohort analysis), and the business impact of your work. Did your recommendation save money? Did your dashboard change how leadership makes decisions? Those are the stories that get interviews.
Python (pandas, scikit-learn), SQL, Tableau or Power BI, statistical modelling, A/B testing, Excel, BigQuery or Snowflake, and data visualisation. If you have experience with machine learning or cloud data tools, include those — they are increasingly expected even for analyst roles.
Listing tools without context is the most common mistake. "Proficient in Python" is meaningless without "Built Python-based demand forecasting model reducing stock waste by £2.4M annually." Always pair the tool with the result. Another mistake is burying technical projects under generic bullet points. Lead with your most impactful analysis.
Data roles attract hundreds of applicants. Make your CV scannable with clear sections and bold keywords. Include a "Technical Skills" or "Tools" section near the top so recruiters can quickly verify you meet the baseline requirements.
Figures in USD. Ranges reflect mid-level experience (3–7 years). Senior roles and major metro areas typically sit at the top of these bands.
Amazon and Meta use structured interviews with SQL and statistics tests — practice window functions and probability basics. Consulting firms like McKinsey or Deloitte Analytics want strong storytelling skills alongside technical ability, so your CV needs to show business impact, not just tools used. Retailers like Tesco or ASOS want analysts who understand customer behaviour metrics — cohort analysis, churn, basket size. Financial services firms like JPMorgan or Barclays want rigour and attention to regulatory data standards.
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