Aishah Anifowoshe

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Aishah Anifowoshe

data analytics · self taught

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Projects

Certified

Self-directed project

Supply Chain Optimization with SAP Business AI

Business AI Associate · AI / ML · October 2026

96/ 100

A ProoV case study · educational project, not employment

Built a tightly scoped supply-chain rescue plan for a German manufacturer: identified the true bottleneck as a single-sourced critical component with roughly two weeks of cover, designed a Joule-style copilot that recommends the next best action with human approval guardrails, and quantified a conservative payback from days recovered plus avoided expedite cost. The board pitch was crisp and decision-oriented, ending in a specific 2-person, 60-day pilot ask with a measurable success target.

Graded against

  • Problem framing & business sense30%
  • Business-AI solution design & guardrails30%
  • ROI and decision quality25%
  • Executive communication15%

Passed · pass mark 60/100

What stood out6
  • Correctly rejected the decoy port delay and focused on the single-sourced component that actually threatens the line
  • Defined a practical copilot output: a drafted PO or reroute for human approval, plus a ranked alert and explicit never-do line
  • Applied the autonomy boundary well, especially by escalating high-value, irreversible actions like air freight and new-supplier moves
  • Made the board ask specific and bounded: a 2-person, 60-day pilot with success defined as detection-to-mitigation under 1 day
  • Leakage-Free Problem Diagnosis
  • Human-in-the-Loop Copilot Design
The work I submitted19 tasks

11 tasks · 7.7k characters · 8 written answers · 615 words

  • SAP Brand Sentiment Pre182 characters
  • Trust Pledge135 characters
  • Diagnose Break300 characters
  • Problem Statement1.2k characters
  • Copilot Spec860 characters
  • Guardrails Sort1.3k characters
  • ROI Payback555 characters
  • India Transfer569 characters
  • Board Pitch1.7k characters
  • Teach Back813 characters
  • SAP Brand Sentiment Post188 characters
  • SAP Brand Sentiment Pre14 words
  • Trust Pledge20 words
  • Diagnose Break23 words
  • Problem Statement180 words
  • Copilot Spec124 words
  • Guardrails Sort127 words
  • ROI Payback56 words
  • India Transfer71 words

Summarised on purpose — the submitted code and writing stay private so this page cannot be reused as an answer key. The full submission sits behind the verified certificate.

Verified certificateTamper-proof · issued by ProoV
Certified

Self-directed project

Business & Sponsorships — The FC Barcelona Case

Data Science · September 2026

84/ 100

A ProoV case study · educational project, not employment

Built an end-to-end commercial sponsorship case for FC Barcelona: analyzed revenue mix, selected Asia-Pacific as the target segment, assembled a €3.0M asset package, and evaluated ElectraX with a performance-weighted recommendation. The final memo is data-backed, acknowledges the 40pp KPI shortfall, and explains the commercial logic and caveats clearly for a non-technical stakeholder.

Graded against

  • Business reasoning & decision quality35%
  • Correct use of data25%
  • Frameworks applied20%
  • Communication & structure20%

Passed · pass mark 55/100

What stood out6
  • Correctly identified Commercial as the controllable revenue lever and tied the 12% growth target to the club’s own commercial stream.
  • Used the Asia-Pacific segment consistently, grounding the recommendation in the saved fan count of 10 and its high engagement.
  • Built a coherent €3.0M package and a performance-weighted ElectraX recommendation that explicitly addressed the 40pp KPI shortfall.
  • Flagged the underperforming content-reach KPI and proposed a concrete make-good / recovery approach in the negotiation messaging.
  • Leakage-Free Segment Selection
  • Framework-Based Commercial Reasoning
The work I submitted20 tasks

12 tasks · 13 lines · Python · 8 written answers · 356 words

  • Revenue Mix Compute521 characters
  • Revenue MixPython · 1.3k characters
  • Fan SegmentationPython · 1.0k characters
  • Package Builder638 characters
  • Coach Usage72 characters
  • KPI ScorecardPython · 712 characters
  • Intern Draft Review158 characters
  • Defence Questions453 characters
  • Spoken Defence2 lines
  • Inbox Responses2.0k characters
  • Mid Season Performance Summary1.2k characters
  • Final Recommendation2.1k characters
  • Revenue Mix Compute40 words
  • Revenue Mix101 words
  • Fan Segmentation53 words
  • Package Builder41 words
  • Coach Usage3 words
  • KPI Scorecard50 words
  • Intern Draft Review1 word
  • Defence Questions67 words

Summarised on purpose — the submitted code and writing stay private so this page cannot be reused as an answer key. The full submission sits behind the verified certificate.

Verified certificateTamper-proof · issued by ProoV
Certified

Self-directed project

Business Analytics Sprint

Data Science · August 2026

91/ 100

A ProoV case study · educational project, not employment

Built an end-to-end profit-paradox analysis: framed hypotheses and KPI drivers, audited the data, wrote correct SQL for category and regional margin analysis, isolated the main profit leaks through a Pareto-style root-cause view, and produced a recovery forecast with board-ready recommendations. The work shows strong business reasoning, solid SQL execution, and clear executive communication.

Graded against

  • Problem Framing & Hypotheses10%
  • Data Analysis & SQL30%
  • Root-Cause & Forecasting25%
  • Dashboard & Visualization15%
  • Executive Communication & Strategy20%

Passed · pass mark 60/100

What stood out6
  • Correctly computed category margin as (revenue − cost) / revenue and ordered categories by margin in SQL.
  • Used a proper join to bring regional discount context into the margin analysis.
  • Identified the main deterioration drivers in the right order: raw-material inflation, logistics inefficiency, and discounting.
  • Translated the analysis into a prioritised recommendation memo with impact and effort framing.
  • Structured Hypothesis Formation
  • Leakage-Free Business Diagnosis
The work I submitted20 tasks

12 tasks · 6.8k characters · 8 written answers · 197 words

  • Hypothesis Sheet365 characters
  • KPI Driver Map174 characters
  • Data Audit100 characters
  • Week1 Update768 characters
  • Sql Category Profit301 characters
  • Sql Region Join369 characters
  • Root Causes158 characters
  • Forecast279 characters
  • Recommendations1.4k characters
  • Boardroom Deck622 characters
  • Stakeholder Qa827 characters
  • Bosch Real Case Study1.5k characters
  • Hypothesis Sheet25 words
  • KPI Driver Map1 word
  • Data Audit4 words
  • Week1 Update107 words
  • Sql Category Profit17 words
  • Sql Region Join32 words
  • Root Causes5 words
  • Forecast6 words

Summarised on purpose — the submitted code and writing stay private so this page cannot be reused as an answer key. The full submission sits behind the verified certificate.

Verified certificateTamper-proof · issued by ProoV
3Projects completed
3Verified certificates
90Average score
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