Operations Data Specialist

• Designed the 0→1 metric system for a conversational product; made useful-conversation rate the north star, unified definitions across teams, and cut decision cycle time 40%.
• Built a retention attribution model (gradient boosting + sequence mining) that flags the drop-off node and a next action. 30-day retention 51% → 62%.
• Shipped an LTV and price-sensitivity dashboard; 12 subscription experiments lifted paid conversion 37% and added $2.1M ARR.
• Added adaptive anomaly detection on activate → engage → pay. Payment-drop discovery fell from hours to 9 minutes; ~$900k recovered in a quarter.
• Built a competitor radar from performance and feature-adoption data; three retention bets lifted weekly active users 28%.

Senior Data Analyst

• Diagnosed a PDP-to-checkout leak. Path attribution in Python found slow load and missing stock alerts; conversion +18% and +$12M quarterly GMV.
• Ran a 6-cell payment A/B on layout, default method, and offer placement. Success rate 68% → 79%; ~$8M abandoned-cart GMV recovered.
• Built a near-line cross-sell engine from browse and cart sequences. Attach rate +2.5 pts, ARPU +11%, ~$15M annual incremental GMV.
• Rebuilt promo monitoring in Tableau with minute-level alerts across warmup, surge, and encore. Caught 3 conversion cliffs in S-tier events and saved $3M+.

Operations Data Analyst

• Stood up a 12-metric daily/weekly pack (DAU, retention, feature penetration). SQL + Sheets cut production from 1 day to 2 hours.
• Segmented 10M+ behavior logs (activation, win-back, high-value). Linked churn thresholds to outreach; high-activity share +8 pts in 6 months.
• Scored activity from entry, depth, and spend; a targeted recall saved 500k at-risk users and lifted next-month retention ~3 pts.
• Forecast dashboards for two S-tier campaigns. Peak DAU landed 25% above organic with no core-service degradation.

Data architecture lead

• Designed 150+ standard events for a 100k-DAU internal messenger — message, A/V, and collab — with one parameter spec.
• Shipped 10+ second-level cockpits. Mean time to locate an incident 25 min → 2 min; critical delivery 99.99%.

Analyst

• Python fulfillment funnel on pick / pack / ship. Isolated outbound delay and sort backlog; mean delivery 32h → 27.2h (−15%); same-day share cleared 67%.

Core member

• LTV tiers plus K-Means/PCA on tens of millions of users. Activation cost −18%, sleep-to-wake conversion +23%, monthly retained actives +11%.

Project lead

• Stood up a crawl + NLP stack across 10+ competitors (store, web, social). ~2M unstructured rows/day into a T+1 Power BI board.
• Flagged an enterprise pivot early; three features shipped first and new-feature adoption beat the historical mean by 16 pts.

Operations Data Specialist

• Designed the 0→1 metric system for a conversational product; made useful-conversation rate the north star, unified definitions across teams, and cut decision cycle time 40%.
• Built a retention attribution model (gradient boosting + sequence mining) that flags the drop-off node and a next action. 30-day retention 51% → 62%.
• Shipped an LTV and price-sensitivity dashboard; 12 subscription experiments lifted paid conversion 37% and added $2.1M ARR.
• Added adaptive anomaly detection on activate → engage → pay. Payment-drop discovery fell from hours to 9 minutes; ~$900k recovered in a quarter.
• Built a competitor radar from performance and feature-adoption data; three retention bets lifted weekly active users 28%.

Senior Data Analyst

• Diagnosed a PDP-to-checkout leak. Path attribution in Python found slow load and missing stock alerts; conversion +18% and +$12M quarterly GMV.
• Ran a 6-cell payment A/B on layout, default method, and offer placement. Success rate 68% → 79%; ~$8M abandoned-cart GMV recovered.
• Built a near-line cross-sell engine from browse and cart sequences. Attach rate +2.5 pts, ARPU +11%, ~$15M annual incremental GMV.
• Rebuilt promo monitoring in Tableau with minute-level alerts across warmup, surge, and encore. Caught 3 conversion cliffs in S-tier events and saved $3M+.

Operations Data Analyst

• Stood up a 12-metric daily/weekly pack (DAU, retention, feature penetration). SQL + Sheets cut production from 1 day to 2 hours.
• Segmented 10M+ behavior logs (activation, win-back, high-value). Linked churn thresholds to outreach; high-activity share +8 pts in 6 months.
• Scored activity from entry, depth, and spend; a targeted recall saved 500k at-risk users and lifted next-month retention ~3 pts.
• Forecast dashboards for two S-tier campaigns. Peak DAU landed 25% above organic with no core-service degradation.

Data architecture lead

• Designed 150+ standard events for a 100k-DAU internal messenger — message, A/V, and collab — with one parameter spec.
• Shipped 10+ second-level cockpits. Mean time to locate an incident 25 min → 2 min; critical delivery 99.99%.

Analyst

• Python fulfillment funnel on pick / pack / ship. Isolated outbound delay and sort backlog; mean delivery 32h → 27.2h (−15%); same-day share cleared 67%.

Core member

• LTV tiers plus K-Means/PCA on tens of millions of users. Activation cost −18%, sleep-to-wake conversion +23%, monthly retained actives +11%.

Project lead

• Stood up a crawl + NLP stack across 10+ competitors (store, web, social). ~2M unstructured rows/day into a T+1 Power BI board.
• Flagged an enterprise pivot early; three features shipped first and new-feature adoption beat the historical mean by 16 pts.

Operations Data Specialist

• Designed the 0→1 metric system for a conversational product; made useful-conversation rate the north star, unified definitions across teams, and cut decision cycle time 40%.
• Built a retention attribution model (gradient boosting + sequence mining) that flags the drop-off node and a next action. 30-day retention 51% → 62%.
• Shipped an LTV and price-sensitivity dashboard; 12 subscription experiments lifted paid conversion 37% and added $2.1M ARR.
• Added adaptive anomaly detection on activate → engage → pay. Payment-drop discovery fell from hours to 9 minutes; ~$900k recovered in a quarter.
• Built a competitor radar from performance and feature-adoption data; three retention bets lifted weekly active users 28%.

Senior Data Analyst

• Diagnosed a PDP-to-checkout leak. Path attribution in Python found slow load and missing stock alerts; conversion +18% and +$12M quarterly GMV.
• Ran a 6-cell payment A/B on layout, default method, and offer placement. Success rate 68% → 79%; ~$8M abandoned-cart GMV recovered.
• Built a near-line cross-sell engine from browse and cart sequences. Attach rate +2.5 pts, ARPU +11%, ~$15M annual incremental GMV.
• Rebuilt promo monitoring in Tableau with minute-level alerts across warmup, surge, and encore. Caught 3 conversion cliffs in S-tier events and saved $3M+.

Operations Data Analyst

• Stood up a 12-metric daily/weekly pack (DAU, retention, feature penetration). SQL + Sheets cut production from 1 day to 2 hours.
• Segmented 10M+ behavior logs (activation, win-back, high-value). Linked churn thresholds to outreach; high-activity share +8 pts in 6 months.
• Scored activity from entry, depth, and spend; a targeted recall saved 500k at-risk users and lifted next-month retention ~3 pts.
• Forecast dashboards for two S-tier campaigns. Peak DAU landed 25% above organic with no core-service degradation.

Data architecture lead

• Designed 150+ standard events for a 100k-DAU internal messenger — message, A/V, and collab — with one parameter spec.
• Shipped 10+ second-level cockpits. Mean time to locate an incident 25 min → 2 min; critical delivery 99.99%.

Analyst

• Python fulfillment funnel on pick / pack / ship. Isolated outbound delay and sort backlog; mean delivery 32h → 27.2h (−15%); same-day share cleared 67%.

Core member

• LTV tiers plus K-Means/PCA on tens of millions of users. Activation cost −18%, sleep-to-wake conversion +23%, monthly retained actives +11%.

Project lead

• Stood up a crawl + NLP stack across 10+ competitors (store, web, social). ~2M unstructured rows/day into a T+1 Power BI board.
• Flagged an enterprise pivot early; three features shipped first and new-feature adoption beat the historical mean by 16 pts.

Operations Data Specialist

• Designed the 0→1 metric system for a conversational product; made useful-conversation rate the north star, unified definitions across teams, and cut decision cycle time 40%.
• Built a retention attribution model (gradient boosting + sequence mining) that flags the drop-off node and a next action. 30-day retention 51% → 62%.
• Shipped an LTV and price-sensitivity dashboard; 12 subscription experiments lifted paid conversion 37% and added $2.1M ARR.
• Added adaptive anomaly detection on activate → engage → pay. Payment-drop discovery fell from hours to 9 minutes; ~$900k recovered in a quarter.
• Built a competitor radar from performance and feature-adoption data; three retention bets lifted weekly active users 28%.

Senior Data Analyst

• Diagnosed a PDP-to-checkout leak. Path attribution in Python found slow load and missing stock alerts; conversion +18% and +$12M quarterly GMV.
• Ran a 6-cell payment A/B on layout, default method, and offer placement. Success rate 68% → 79%; ~$8M abandoned-cart GMV recovered.
• Built a near-line cross-sell engine from browse and cart sequences. Attach rate +2.5 pts, ARPU +11%, ~$15M annual incremental GMV.
• Rebuilt promo monitoring in Tableau with minute-level alerts across warmup, surge, and encore. Caught 3 conversion cliffs in S-tier events and saved $3M+.

Operations Data Analyst

• Stood up a 12-metric daily/weekly pack (DAU, retention, feature penetration). SQL + Sheets cut production from 1 day to 2 hours.
• Segmented 10M+ behavior logs (activation, win-back, high-value). Linked churn thresholds to outreach; high-activity share +8 pts in 6 months.
• Scored activity from entry, depth, and spend; a targeted recall saved 500k at-risk users and lifted next-month retention ~3 pts.
• Forecast dashboards for two S-tier campaigns. Peak DAU landed 25% above organic with no core-service degradation.

Data architecture lead

• Designed 150+ standard events for a 100k-DAU internal messenger — message, A/V, and collab — with one parameter spec.
• Shipped 10+ second-level cockpits. Mean time to locate an incident 25 min → 2 min; critical delivery 99.99%.

Analyst

• Python fulfillment funnel on pick / pack / ship. Isolated outbound delay and sort backlog; mean delivery 32h → 27.2h (−15%); same-day share cleared 67%.

Core member

• LTV tiers plus K-Means/PCA on tens of millions of users. Activation cost −18%, sleep-to-wake conversion +23%, monthly retained actives +11%.

Project lead

• Stood up a crawl + NLP stack across 10+ competitors (store, web, social). ~2M unstructured rows/day into a T+1 Power BI board.
• Flagged an enterprise pivot early; three features shipped first and new-feature adoption beat the historical mean by 16 pts.

Operations Data Specialist

• Designed the 0→1 metric system for a conversational product; made useful-conversation rate the north star, unified definitions across teams, and cut decision cycle time 40%.
• Built a retention attribution model (gradient boosting + sequence mining) that flags the drop-off node and a next action. 30-day retention 51% → 62%.
• Shipped an LTV and price-sensitivity dashboard; 12 subscription experiments lifted paid conversion 37% and added $2.1M ARR.
• Added adaptive anomaly detection on activate → engage → pay. Payment-drop discovery fell from hours to 9 minutes; ~$900k recovered in a quarter.
• Built a competitor radar from performance and feature-adoption data; three retention bets lifted weekly active users 28%.

Senior Data Analyst

• Diagnosed a PDP-to-checkout leak. Path attribution in Python found slow load and missing stock alerts; conversion +18% and +$12M quarterly GMV.
• Ran a 6-cell payment A/B on layout, default method, and offer placement. Success rate 68% → 79%; ~$8M abandoned-cart GMV recovered.
• Built a near-line cross-sell engine from browse and cart sequences. Attach rate +2.5 pts, ARPU +11%, ~$15M annual incremental GMV.
• Rebuilt promo monitoring in Tableau with minute-level alerts across warmup, surge, and encore. Caught 3 conversion cliffs in S-tier events and saved $3M+.

Operations Data Analyst

• Stood up a 12-metric daily/weekly pack (DAU, retention, feature penetration). SQL + Sheets cut production from 1 day to 2 hours.
• Segmented 10M+ behavior logs (activation, win-back, high-value). Linked churn thresholds to outreach; high-activity share +8 pts in 6 months.
• Scored activity from entry, depth, and spend; a targeted recall saved 500k at-risk users and lifted next-month retention ~3 pts.
• Forecast dashboards for two S-tier campaigns. Peak DAU landed 25% above organic with no core-service degradation.

Data architecture lead

• Designed 150+ standard events for a 100k-DAU internal messenger — message, A/V, and collab — with one parameter spec.
• Shipped 10+ second-level cockpits. Mean time to locate an incident 25 min → 2 min; critical delivery 99.99%.

Analyst

• Python fulfillment funnel on pick / pack / ship. Isolated outbound delay and sort backlog; mean delivery 32h → 27.2h (−15%); same-day share cleared 67%.

Core member

• LTV tiers plus K-Means/PCA on tens of millions of users. Activation cost −18%, sleep-to-wake conversion +23%, monthly retained actives +11%.

Project lead

• Stood up a crawl + NLP stack across 10+ competitors (store, web, social). ~2M unstructured rows/day into a T+1 Power BI board.
• Flagged an enterprise pivot early; three features shipped first and new-feature adoption beat the historical mean by 16 pts.

Operations Data Specialist

• Designed the 0→1 metric system for a conversational product; made useful-conversation rate the north star, unified definitions across teams, and cut decision cycle time 40%.
• Built a retention attribution model (gradient boosting + sequence mining) that flags the drop-off node and a next action. 30-day retention 51% → 62%.
• Shipped an LTV and price-sensitivity dashboard; 12 subscription experiments lifted paid conversion 37% and added $2.1M ARR.
• Added adaptive anomaly detection on activate → engage → pay. Payment-drop discovery fell from hours to 9 minutes; ~$900k recovered in a quarter.
• Built a competitor radar from performance and feature-adoption data; three retention bets lifted weekly active users 28%.

Senior Data Analyst

• Diagnosed a PDP-to-checkout leak. Path attribution in Python found slow load and missing stock alerts; conversion +18% and +$12M quarterly GMV.
• Ran a 6-cell payment A/B on layout, default method, and offer placement. Success rate 68% → 79%; ~$8M abandoned-cart GMV recovered.
• Built a near-line cross-sell engine from browse and cart sequences. Attach rate +2.5 pts, ARPU +11%, ~$15M annual incremental GMV.
• Rebuilt promo monitoring in Tableau with minute-level alerts across warmup, surge, and encore. Caught 3 conversion cliffs in S-tier events and saved $3M+.

Operations Data Analyst

• Stood up a 12-metric daily/weekly pack (DAU, retention, feature penetration). SQL + Sheets cut production from 1 day to 2 hours.
• Segmented 10M+ behavior logs (activation, win-back, high-value). Linked churn thresholds to outreach; high-activity share +8 pts in 6 months.
• Scored activity from entry, depth, and spend; a targeted recall saved 500k at-risk users and lifted next-month retention ~3 pts.
• Forecast dashboards for two S-tier campaigns. Peak DAU landed 25% above organic with no core-service degradation.

Data architecture lead

• Designed 150+ standard events for a 100k-DAU internal messenger — message, A/V, and collab — with one parameter spec.
• Shipped 10+ second-level cockpits. Mean time to locate an incident 25 min → 2 min; critical delivery 99.99%.

Analyst

• Python fulfillment funnel on pick / pack / ship. Isolated outbound delay and sort backlog; mean delivery 32h → 27.2h (−15%); same-day share cleared 67%.

Core member

• LTV tiers plus K-Means/PCA on tens of millions of users. Activation cost −18%, sleep-to-wake conversion +23%, monthly retained actives +11%.

Project lead

• Stood up a crawl + NLP stack across 10+ competitors (store, web, social). ~2M unstructured rows/day into a T+1 Power BI board.
• Flagged an enterprise pivot early; three features shipped first and new-feature adoption beat the historical mean by 16 pts.

Operations Data Specialist

• Designed the 0→1 metric system for a conversational product; made useful-conversation rate the north star, unified definitions across teams, and cut decision cycle time 40%.
• Built a retention attribution model (gradient boosting + sequence mining) that flags the drop-off node and a next action. 30-day retention 51% → 62%.
• Shipped an LTV and price-sensitivity dashboard; 12 subscription experiments lifted paid conversion 37% and added $2.1M ARR.
• Added adaptive anomaly detection on activate → engage → pay. Payment-drop discovery fell from hours to 9 minutes; ~$900k recovered in a quarter.
• Built a competitor radar from performance and feature-adoption data; three retention bets lifted weekly active users 28%.

Senior Data Analyst

• Diagnosed a PDP-to-checkout leak. Path attribution in Python found slow load and missing stock alerts; conversion +18% and +$12M quarterly GMV.
• Ran a 6-cell payment A/B on layout, default method, and offer placement. Success rate 68% → 79%; ~$8M abandoned-cart GMV recovered.
• Built a near-line cross-sell engine from browse and cart sequences. Attach rate +2.5 pts, ARPU +11%, ~$15M annual incremental GMV.
• Rebuilt promo monitoring in Tableau with minute-level alerts across warmup, surge, and encore. Caught 3 conversion cliffs in S-tier events and saved $3M+.

Operations Data Analyst

• Stood up a 12-metric daily/weekly pack (DAU, retention, feature penetration). SQL + Sheets cut production from 1 day to 2 hours.
• Segmented 10M+ behavior logs (activation, win-back, high-value). Linked churn thresholds to outreach; high-activity share +8 pts in 6 months.
• Scored activity from entry, depth, and spend; a targeted recall saved 500k at-risk users and lifted next-month retention ~3 pts.
• Forecast dashboards for two S-tier campaigns. Peak DAU landed 25% above organic with no core-service degradation.

Data architecture lead

• Designed 150+ standard events for a 100k-DAU internal messenger — message, A/V, and collab — with one parameter spec.
• Shipped 10+ second-level cockpits. Mean time to locate an incident 25 min → 2 min; critical delivery 99.99%.

Analyst

• Python fulfillment funnel on pick / pack / ship. Isolated outbound delay and sort backlog; mean delivery 32h → 27.2h (−15%); same-day share cleared 67%.

Core member

• LTV tiers plus K-Means/PCA on tens of millions of users. Activation cost −18%, sleep-to-wake conversion +23%, monthly retained actives +11%.

Project lead

• Stood up a crawl + NLP stack across 10+ competitors (store, web, social). ~2M unstructured rows/day into a T+1 Power BI board.
• Flagged an enterprise pivot early; three features shipped first and new-feature adoption beat the historical mean by 16 pts.

Operations Data Specialist

• Designed the 0→1 metric system for a conversational product; made useful-conversation rate the north star, unified definitions across teams, and cut decision cycle time 40%.
• Built a retention attribution model (gradient boosting + sequence mining) that flags the drop-off node and a next action. 30-day retention 51% → 62%.
• Shipped an LTV and price-sensitivity dashboard; 12 subscription experiments lifted paid conversion 37% and added $2.1M ARR.
• Added adaptive anomaly detection on activate → engage → pay. Payment-drop discovery fell from hours to 9 minutes; ~$900k recovered in a quarter.
• Built a competitor radar from performance and feature-adoption data; three retention bets lifted weekly active users 28%.

Senior Data Analyst

• Diagnosed a PDP-to-checkout leak. Path attribution in Python found slow load and missing stock alerts; conversion +18% and +$12M quarterly GMV.
• Ran a 6-cell payment A/B on layout, default method, and offer placement. Success rate 68% → 79%; ~$8M abandoned-cart GMV recovered.
• Built a near-line cross-sell engine from browse and cart sequences. Attach rate +2.5 pts, ARPU +11%, ~$15M annual incremental GMV.
• Rebuilt promo monitoring in Tableau with minute-level alerts across warmup, surge, and encore. Caught 3 conversion cliffs in S-tier events and saved $3M+.

Operations Data Analyst

• Stood up a 12-metric daily/weekly pack (DAU, retention, feature penetration). SQL + Sheets cut production from 1 day to 2 hours.
• Segmented 10M+ behavior logs (activation, win-back, high-value). Linked churn thresholds to outreach; high-activity share +8 pts in 6 months.
• Scored activity from entry, depth, and spend; a targeted recall saved 500k at-risk users and lifted next-month retention ~3 pts.
• Forecast dashboards for two S-tier campaigns. Peak DAU landed 25% above organic with no core-service degradation.

Data architecture lead

• Designed 150+ standard events for a 100k-DAU internal messenger — message, A/V, and collab — with one parameter spec.
• Shipped 10+ second-level cockpits. Mean time to locate an incident 25 min → 2 min; critical delivery 99.99%.

Analyst

• Python fulfillment funnel on pick / pack / ship. Isolated outbound delay and sort backlog; mean delivery 32h → 27.2h (−15%); same-day share cleared 67%.

Core member

• LTV tiers plus K-Means/PCA on tens of millions of users. Activation cost −18%, sleep-to-wake conversion +23%, monthly retained actives +11%.

Project lead

• Stood up a crawl + NLP stack across 10+ competitors (store, web, social). ~2M unstructured rows/day into a T+1 Power BI board.
• Flagged an enterprise pivot early; three features shipped first and new-feature adoption beat the historical mean by 16 pts.

Operations Data Specialist

• Designed the 0→1 metric system for a conversational product; made useful-conversation rate the north star, unified definitions across teams, and cut decision cycle time 40%.
• Built a retention attribution model (gradient boosting + sequence mining) that flags the drop-off node and a next action. 30-day retention 51% → 62%.
• Shipped an LTV and price-sensitivity dashboard; 12 subscription experiments lifted paid conversion 37% and added $2.1M ARR.
• Added adaptive anomaly detection on activate → engage → pay. Payment-drop discovery fell from hours to 9 minutes; ~$900k recovered in a quarter.
• Built a competitor radar from performance and feature-adoption data; three retention bets lifted weekly active users 28%.

Senior Data Analyst

• Diagnosed a PDP-to-checkout leak. Path attribution in Python found slow load and missing stock alerts; conversion +18% and +$12M quarterly GMV.
• Ran a 6-cell payment A/B on layout, default method, and offer placement. Success rate 68% → 79%; ~$8M abandoned-cart GMV recovered.
• Built a near-line cross-sell engine from browse and cart sequences. Attach rate +2.5 pts, ARPU +11%, ~$15M annual incremental GMV.
• Rebuilt promo monitoring in Tableau with minute-level alerts across warmup, surge, and encore. Caught 3 conversion cliffs in S-tier events and saved $3M+.

Operations Data Analyst

• Stood up a 12-metric daily/weekly pack (DAU, retention, feature penetration). SQL + Sheets cut production from 1 day to 2 hours.
• Segmented 10M+ behavior logs (activation, win-back, high-value). Linked churn thresholds to outreach; high-activity share +8 pts in 6 months.
• Scored activity from entry, depth, and spend; a targeted recall saved 500k at-risk users and lifted next-month retention ~3 pts.
• Forecast dashboards for two S-tier campaigns. Peak DAU landed 25% above organic with no core-service degradation.

Data architecture lead

• Designed 150+ standard events for a 100k-DAU internal messenger — message, A/V, and collab — with one parameter spec.
• Shipped 10+ second-level cockpits. Mean time to locate an incident 25 min → 2 min; critical delivery 99.99%.

Analyst

• Python fulfillment funnel on pick / pack / ship. Isolated outbound delay and sort backlog; mean delivery 32h → 27.2h (−15%); same-day share cleared 67%.

Core member

• LTV tiers plus K-Means/PCA on tens of millions of users. Activation cost −18%, sleep-to-wake conversion +23%, monthly retained actives +11%.

Project lead

• Stood up a crawl + NLP stack across 10+ competitors (store, web, social). ~2M unstructured rows/day into a T+1 Power BI board.
• Flagged an enterprise pivot early; three features shipped first and new-feature adoption beat the historical mean by 16 pts.

Operations Data Specialist

• Designed the 0→1 metric system for a conversational product; made useful-conversation rate the north star, unified definitions across teams, and cut decision cycle time 40%.
• Built a retention attribution model (gradient boosting + sequence mining) that flags the drop-off node and a next action. 30-day retention 51% → 62%.
• Shipped an LTV and price-sensitivity dashboard; 12 subscription experiments lifted paid conversion 37% and added $2.1M ARR.
• Added adaptive anomaly detection on activate → engage → pay. Payment-drop discovery fell from hours to 9 minutes; ~$900k recovered in a quarter.
• Built a competitor radar from performance and feature-adoption data; three retention bets lifted weekly active users 28%.

Senior Data Analyst

• Diagnosed a PDP-to-checkout leak. Path attribution in Python found slow load and missing stock alerts; conversion +18% and +$12M quarterly GMV.
• Ran a 6-cell payment A/B on layout, default method, and offer placement. Success rate 68% → 79%; ~$8M abandoned-cart GMV recovered.
• Built a near-line cross-sell engine from browse and cart sequences. Attach rate +2.5 pts, ARPU +11%, ~$15M annual incremental GMV.
• Rebuilt promo monitoring in Tableau with minute-level alerts across warmup, surge, and encore. Caught 3 conversion cliffs in S-tier events and saved $3M+.

Operations Data Analyst

• Stood up a 12-metric daily/weekly pack (DAU, retention, feature penetration). SQL + Sheets cut production from 1 day to 2 hours.
• Segmented 10M+ behavior logs (activation, win-back, high-value). Linked churn thresholds to outreach; high-activity share +8 pts in 6 months.
• Scored activity from entry, depth, and spend; a targeted recall saved 500k at-risk users and lifted next-month retention ~3 pts.
• Forecast dashboards for two S-tier campaigns. Peak DAU landed 25% above organic with no core-service degradation.

Data architecture lead

• Designed 150+ standard events for a 100k-DAU internal messenger — message, A/V, and collab — with one parameter spec.
• Shipped 10+ second-level cockpits. Mean time to locate an incident 25 min → 2 min; critical delivery 99.99%.

Analyst

• Python fulfillment funnel on pick / pack / ship. Isolated outbound delay and sort backlog; mean delivery 32h → 27.2h (−15%); same-day share cleared 67%.

Core member

• LTV tiers plus K-Means/PCA on tens of millions of users. Activation cost −18%, sleep-to-wake conversion +23%, monthly retained actives +11%.

Project lead

• Stood up a crawl + NLP stack across 10+ competitors (store, web, social). ~2M unstructured rows/day into a T+1 Power BI board.
• Flagged an enterprise pivot early; three features shipped first and new-feature adoption beat the historical mean by 16 pts.

Operations Data Specialist

• Designed the 0→1 metric system for a conversational product; made useful-conversation rate the north star, unified definitions across teams, and cut decision cycle time 40%.
• Built a retention attribution model (gradient boosting + sequence mining) that flags the drop-off node and a next action. 30-day retention 51% → 62%.
• Shipped an LTV and price-sensitivity dashboard; 12 subscription experiments lifted paid conversion 37% and added $2.1M ARR.
• Added adaptive anomaly detection on activate → engage → pay. Payment-drop discovery fell from hours to 9 minutes; ~$900k recovered in a quarter.
• Built a competitor radar from performance and feature-adoption data; three retention bets lifted weekly active users 28%.

Senior Data Analyst

• Diagnosed a PDP-to-checkout leak. Path attribution in Python found slow load and missing stock alerts; conversion +18% and +$12M quarterly GMV.
• Ran a 6-cell payment A/B on layout, default method, and offer placement. Success rate 68% → 79%; ~$8M abandoned-cart GMV recovered.
• Built a near-line cross-sell engine from browse and cart sequences. Attach rate +2.5 pts, ARPU +11%, ~$15M annual incremental GMV.
• Rebuilt promo monitoring in Tableau with minute-level alerts across warmup, surge, and encore. Caught 3 conversion cliffs in S-tier events and saved $3M+.

Operations Data Analyst

• Stood up a 12-metric daily/weekly pack (DAU, retention, feature penetration). SQL + Sheets cut production from 1 day to 2 hours.
• Segmented 10M+ behavior logs (activation, win-back, high-value). Linked churn thresholds to outreach; high-activity share +8 pts in 6 months.
• Scored activity from entry, depth, and spend; a targeted recall saved 500k at-risk users and lifted next-month retention ~3 pts.
• Forecast dashboards for two S-tier campaigns. Peak DAU landed 25% above organic with no core-service degradation.

Data architecture lead

• Designed 150+ standard events for a 100k-DAU internal messenger — message, A/V, and collab — with one parameter spec.
• Shipped 10+ second-level cockpits. Mean time to locate an incident 25 min → 2 min; critical delivery 99.99%.

Analyst

• Python fulfillment funnel on pick / pack / ship. Isolated outbound delay and sort backlog; mean delivery 32h → 27.2h (−15%); same-day share cleared 67%.