Jeremy Rieunier

Data Analyst & Analytics Engineer

Sep. 2025 - Present · Remote

Building the data layer behind product-led growth for a hospitality management platform.

Built a revenue-per-area benchmark suite (m² and ft²) that positions ~6,500 hotels against their peer group, forming the analytical backbone of the company-wide product-led growth program.
Owned 15+ dbt models end to end, covering area-normalized benchmarks, point-in-time snapshots, and peer-group segmentation, with strict attention to currency-comparable metrics.
Operationalized the benchmarks into the customer success platform, feeding product-qualified lead (PQL) scoring and in-product growth campaigns.
Closed the loop from models to consumption, building and maintaining data products that turn benchmarks into stakeholder-facing insights.
Built internal tooling and documentation in Hex, including AI and LLM context assets, to speed up the data team's workflows and make analyses reproducible.

Jun. 2023 - Sep. 2024 · Valencia, Spain

Established product analytics capabilities for an HR SaaS company.

Trained product teams on the North Star Metric framework and collaboratively built metric trees for 20+ product features, defining critical user journeys and success metrics.
Built a data platform that extracts data from PostgreSQL production databases into BigQuery, implements medallion architecture in dbt, and connects to Metabase for self-service visualization.
Defined event tracking taxonomy and data contracts on ClickUp, partnering with engineers to ensure consistent implementation across the product and maintain data integrity.
Conducted in-depth product analyses using SQL and Amplitude, performing cohort, funnel, and retention studies that revealed key adoption barriers and guided feature prioritization decisions.
Mentored product managers and designers on self-serve analytics tools, increasing team's analytics adoption by 150% and reducing ad-hoc requests by 60% in 8 weeks.

Sep 2022 - Jun 2023 · Remote

Implemented data infrastructures and tracking plans for ecommerce SaaS businesses.

Developed comprehensive event taxonomies and tracking plans using Amplitude and Segment, collaborating with engineering teams to ensure consistent implementation across features.
Built modular dbt data models that transformed subscription data into actionable product analytics, enabling teams to identify patterns between product usage and retention metrics.

Nov. 2018 - Dec. 2022 · Remote

Operated an analytics consultancy helping CPG and beauty brands optimize activation and retention strategies.

Architected end-to-end data infrastructures using Google Cloud Platform, implementing ELT pipelines with Stitch/Fivetran, transformation with dbt, and visualization layers with Looker to enable comprehensive ecommerce analytics.
Designed modular data models in BigQuery that enabled advanced customer analysis, including cohort retention, RFM segmentation, and purchase pattern identification, revealing key drivers of lifetime value.
Implemented customer feedback systems combining post-purchase surveys with Python-based NLP analysis, transforming qualitative feedback into quantifiable insights that informed messaging, positioning, and product development priorities.
Developed predictive models based on historical purchase data, enabling proactive CRM campaign planning that addressed forecasted performance gaps and ensured achievement of revenue targets.

May 2016 - Nov. 2018 · Remote

Provided growth marketing strategies for lifestyle DTC brands on Shopify.

Architected tracking solutions using Segment, Google Tag Manager, and Google Analytics, creating centralized data collection systems that improved attribution accuracy and unified cross-channel customer journey data.
Designed custom attribution models in Google Sheets that provided clients with accurate ROAS calculations, enabling more efficient allocation of marketing budgets across channels.
Developed lifecycle email automation strategies using Klaviyo, driving up to 20% of monthly revenue through targeted behavioral triggers and engagement-based segmentation.

Jan. 2015 - May 2016 · London, UK

Led customer acquisition, CRM, and analytics for an ecommerce menswear brand.

Implemented cross-platform tracking using Google Analytics and JavaScript, creating a unified view of the customer journey from acquisition channels through post-purchase behaviors.
Developed automated dashboards in Google Sheets using Zapier for data ingestion and Google Apps Script for transformation, improving decision-making and reducing reporting time.
Enhanced customer activation by integrating Klaviyo's JS API with SPOKE's fit finder quiz, enabling personalized product recommendations that increased conversion rates by 15% and improved first-time buyer experience.

Established a product analytics infrastructure for measuring performance across features.

Applied the North Star metrics framework across features, defining key success metrics and creating measurement alignment between product, engineering, and executive teams.
Collaborated with DevOps to build ETL/ELT pipelines that extract data from PostgreSQL production databases and third-party platforms (Swann and Chargebee) to BigQuery.
Implemented medallion architecture in dbt to transform raw data into analysis-ready datasets, with proper data quality testing and documentation.
Created self-serve dashboards that enable product teams to identify adoption barriers and optimization opportunities.

Built data pipelines connecting financial and product analytics systems for comprehensive subscription performance analysis.

Used Fivetran to extract Stripe subscription data into BigQuery, ensuring reliable capture of payment events, plan changes, and customer lifecycle transitions.
Developed modular dbt models that transform raw Stripe transactions into standardized event streams compatible with Amplitude's event schema.
Built custom metrics in dbt that calculate key subscription indicators, including MRR movement, customer lifetime value, and retention cohorts.
Synchronized transformed events and metrics back to Amplitude, enabling product teams to analyze correlations between feature usage patterns and subscription outcomes.

Developed a customer lifetime value analysis framework using Python to model and visualize revenue patterns over time.

Implemented exponential decay regression modeling to quantify how customer value evolves over time, enabling more accurate revenue forecasting.
Created cohort analysis visualizations tracking multiple customer segments across various months, revealing distinct retention patterns.
Built interactive time series visualizations comparing new vs. returning revenue over time, uncovering seasonal patterns and growth trends.

Sep 2011 - Jul 2014 · Pau Business School, France

Languages: Native French, bilingual in English and Spanish.
SQL & Databases: Databricks, BigQuery, PostgreSQL.
BI & Visualization: Hex, Looker, Metabase, Amplitude.
ETL/ELT & Data Pipelines: Fivetran, Stitch, Segment.
Data Modeling: dbt, medallion architecture, dimensional modeling, metrics definition.
Programming: Python (pandas, NumPy, scikit-learn, Prophet), JavaScript, Google Apps Script, Git.