Data Analyst

Michael Scott

Data Analyst, former paper salesman. I know what a sales team actually needs from a dashboard, because I used to be the one ignoring it. I make SQL look easy and hard truths sound like a 'that's what she said.'

Open to workParis, FR

Projects

Experience

9yrs

3 roles

Education

Data Analyst path

D8A Academy

Skills

SQL

Expert

Excel

Expert

BigQuery

Advanced

Python

Advanced

Pandas

Advanced

Power BI

Advanced

DAX

Intermediate

Looker

Intermediate

GA4

Intermediate

dbt

Beginner

skills

Expert2

Advanced4

Intermediate3

Beginner1

Projects

#ProjectStackStatus

01E-commerce sales analysis in SQLAnswered twelve business questions on an e-commerce database with JOINs, CTEs and window functions: revenue by month and category, repeat-purchase rate, average time between first and second order. Ranked customers by lifetime value and found that 9% of them made 41% of the revenue.

SQLPostgreSQL

02Customer churn exploration in PythonCleaned a subscription dataset with Pandas (missing values, inconsistent plan names, duplicated accounts), then explored who cancels and when. The main finding: most cancellations happen in the first 60 days, and customers who never used the mobile app churned at twice the rate. Charted with Matplotlib.

PythonPandas

03GA4 funnel and retention in BigQueryRebuilt the purchase funnel from raw GA4 event data exported to BigQuery: sessions, product views, add to cart, checkout, purchase. Measured the drop at each step by device and built weekly retention cohorts. Mobile checkout lost 2.5x more users than desktop at the payment step.

BigQueryGA4

04Executive KPI dashboard in Power BIPower BI model with a sales fact table and date, product and store dimensions. DAX measures for revenue, margin, year-over-year growth and the share of revenue per channel. One executive page, one page per region, with bookmarks for the monthly review.

Power BIDAX

05Vélib' station demand in ParisPulled a year of Paris bike-share station data from the open data portal, loaded it into PostgreSQL and looked at which stations run empty, and when. Morning commute empties the residential stations in the east by 8:30. Wrote it up as a short blog post with maps.

PythonPandasSQL

Personal

Experience & education

20142016201920212024Now

Data Analyst · ManoManoWork2024 — Present

Analyst for the French marketplace category team. I own the weekly performance report (BigQuery + Looker), run ad-hoc analyses for six category managers, and built the seller-churn alert that flags sellers whose sales drop 30% month over month.

Junior Data Analyst · Fnac DartyWork2022 — 2024

Built and maintained the e-commerce team's Power BI reports (traffic, conversion, revenue by channel). Automated the daily sales extract with Python, which saved the team about two hours a day of manual Excel work.

Data Analyst path · D8A AcademyEducation2022

Four validated projects: SQL, Python for analysis, BigQuery and GA4, Power BI.

Sales Representative · Dunder MifflinWork2017 — 2022

Regional paper and office supplies sales. Consistently in the top three of the branch. Learned the business before learning the data, which is still the most useful thing on this page.

BSc Business Administration · Université Paris NanterreEducation2014 - 2017

Skill coverage

	BigQuery	DAX	GA4	Pandas	PostgreSQL	Power BI	Python	SQL
E-commerce sales analysis in SQL
Customer churn exploration in Python
GA4 funnel and retention in BigQuery
Executive KPI dashboard in Power BI
Vélib' station demand in Paris

Filled cell = skill used in that project.