Data Analyst
A data analyst resume focused on SQL depth, decision support, dashboards, automation, and business recommendations.
Elena Petrov
Data Analyst · Business Intelligence · Strategic Insights
Chicago, IL | [email protected] | +1 (312) 555-0167 | https://elenapetrov.dev
LinkedIn: https://linkedin.com/in/elenapetrov | Tableau: https://public.tableau.com/profile/elenapetrov
Summary
Data analyst with 6 years transforming raw data into actionable business insights. Expertise in SQL, Python, and business intelligence tools. Built dashboards and reports used by 500+ stakeholders. Proven ability to partner with leadership, identify trends, and drive data-informed decision making. Strong communicator who translates technical findings for non-technical audiences.
Experience
Senior Data Analyst
RetailTech Corp — Chicago, IL
2021 – 2026
- Developed 25+ dashboards in Tableau serving 200+ daily active users across organization
- Analyzed user behavior data (2.3B events) to identify drop-off points; insights drove 18% improvement in conversion
- Built automated reporting pipeline saving 40 hours/month of manual work using Python and SQL
- Partnered with product team on A/B testing analysis; designed statistical framework for 50+ experiments
- Mentored 2 junior analysts on SQL optimization and presentation skills
Tech: SQL, Python, Tableau, Google Analytics, AWS
Data Analyst
E-Commerce Analytics — Remote
2018 – 2021
- Created company's first attribution model; improved marketing ROI measurement accuracy from 60% to 92%
- Analyzed customer cohorts; identified key retention drivers used by product team for prioritization
- Built real-time monitoring dashboard for KPIs; reduced reporting cycles from weekly to hourly
- Conducted 20+ ad-hoc analyses for C-suite executives; influenced $3M in budget allocation decisions
Tech: SQL, Excel, Tableau, Google Analytics, Python
Projects
Customer Lifetime Value Model
Predictive model forecasting customer LTV with 85% accuracy
- Used Python (scikit-learn) to build logistic regression model
- Integrated with CRM system for automated scoring of new customers
- Enabled targeted retention campaigns, improving retention by 12%
Marketing Spend Optimization Analysis
Multi-touch attribution analysis recommending channel budget reallocation
- Analyzed 500K transactions across 8 channels with 6-month lookback window
- Used Markov model to determine true channel contribution
- Recommended budget reallocation projected to increase ROI by 15%
Skills
Analytics & Databases
SQL (Advanced), PostgreSQL, Google Analytics, Data Warehousing, ETL
Programming & Statistics
Python, R, Statistical Analysis, A/B Testing, Experimentation
Visualization & Tools
Tableau, Looker, Power BI, Excel (Advanced), Google Sheets
Business Skills
Business Acumen, Problem Solving, Presentation, Stakeholder Communication, Project Management
Education
MS Data Science
Northwestern University — Evanston, IL
2016 – 2018
BS Mathematics
University of Chicago — Chicago, IL
2012 – 2016
Languages
Elena Petrov
Data Analyst · Business Intelligence · Strategic Insights
Chicago, IL | [email protected] | +1 (312) 555-0167 | https://elenapetrov.dev
LinkedIn: https://linkedin.com/in/elenapetrov | Tableau: https://public.tableau.com/profile/elenapetrov
Summary
Data analyst with 6 years transforming raw data into actionable business insights. Expertise in SQL, Python, and business intelligence tools. Built dashboards and reports used by 500+ stakeholders. Proven ability to partner with leadership, identify trends, and drive data-informed decision making. Strong communicator who translates technical findings for non-technical audiences.
Experience
Senior Data Analyst
RetailTech Corp — Chicago, IL
2021 – 2026
- Developed 25+ dashboards in Tableau serving 200+ daily active users across organization
- Analyzed user behavior data (2.3B events) to identify drop-off points; insights drove 18% improvement in conversion
- Built automated reporting pipeline saving 40 hours/month of manual work using Python and SQL
- Partnered with product team on A/B testing analysis; designed statistical framework for 50+ experiments
- Mentored 2 junior analysts on SQL optimization and presentation skills
Tech: SQL, Python, Tableau, Google Analytics, AWS
Data Analyst
E-Commerce Analytics — Remote
2018 – 2021
- Created company's first attribution model; improved marketing ROI measurement accuracy from 60% to 92%
- Analyzed customer cohorts; identified key retention drivers used by product team for prioritization
- Built real-time monitoring dashboard for KPIs; reduced reporting cycles from weekly to hourly
- Conducted 20+ ad-hoc analyses for C-suite executives; influenced $3M in budget allocation decisions
Tech: SQL, Excel, Tableau, Google Analytics, Python
Projects
Customer Lifetime Value Model
Predictive model forecasting customer LTV with 85% accuracy
- Used Python (scikit-learn) to build logistic regression model
- Integrated with CRM system for automated scoring of new customers
- Enabled targeted retention campaigns, improving retention by 12%
Marketing Spend Optimization Analysis
Multi-touch attribution analysis recommending channel budget reallocation
- Analyzed 500K transactions across 8 channels with 6-month lookback window
- Used Markov model to determine true channel contribution
- Recommended budget reallocation projected to increase ROI by 15%
Skills
Analytics & Databases
SQL (Advanced), PostgreSQL, Google Analytics, Data Warehousing, ETL
Programming & Statistics
Python, R, Statistical Analysis, A/B Testing, Experimentation
Visualization & Tools
Tableau, Looker, Power BI, Excel (Advanced), Google Sheets
Business Skills
Business Acumen, Problem Solving, Presentation, Stakeholder Communication, Project Management
Education
MS Data Science
Northwestern University — Evanston, IL
2016 – 2018
BS Mathematics
University of Chicago — Chicago, IL
2012 – 2016
Languages
What hiring teams look for
Data analysts help teams make better decisions. Hiring managers want to see SQL fluency, analytical rigor, stakeholder communication, clear dashboards, automation, and the ability to turn ambiguous business questions into useful recommendations.
Why this resume works
This example connects analytical work to decisions and operational improvements. It shows dashboards, analysis, automation, and stakeholder enablement, but it does not stop at tools. The value comes from how the analysis changed team behavior or business outcomes.
How to structure this resume
Structure the resume around business impact and analytical method. Mention tools like SQL, Tableau, Python, or Excel in context, then explain the question answered, the dataset or workflow improved, and the decision enabled. Keep dashboards and automation tied to usage or time saved.
What to avoid
Avoid writing only “built dashboards” or “analyzed data.” Those phrases need context. Include adoption, decision impact, accuracy, automation, or stakeholder outcomes. Do not overemphasize data volume if the business value is unclear.
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LinkedIn: https://linkedin.com/in/jordansmith | GitHub: https://github.com/jordansmith
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