Four teams across India, the UK and the UAE. For each, the exact problem they faced, what I did about it, the measurable result, and the tools I used. See the project case studies →
Apr 2026 — PresentDubai, UAE
Confidential — Data Analyst, Sales & Logistics
Sales & logistics analytics across a 60+ country B2B-distributor and B2C-residential network: CRM pipeline strategy, vendor management, performance reporting and lead operations.
Tools · Odoo CRM · Microsoft Excel · Google Sheets · Microsoft Word · Meta Ads
Leadership couldn't see where revenue stalled
Deal stages were inconsistent across a 60+ country footprint and a 10-person sales team. I architected a standardised 16-stage Odoo CRM pipeline spanning B2B distributor and B2C residential segments, with clear definitions for every stage.
▲ +45% pipeline visibility across the 4 core funnel metrics
Odoo CRMFunnel design
Distributors weren't re-ordering predictably
I designed a three-tier vendor classification (Platinum, Gold, Silver) with defined contact cadences and re-purchase triggers across African, Asian and Middle-Eastern markets.
▲ +30% repeat-order rate · steadier inbound for logistics planning
Odoo CRMSegmentation
Weekly reporting ate the team's time
I built a Month-on-Month salesperson performance dashboard in Excel with per-rep drilldowns on the four funnel metrics, surfacing conversion gaps that fed coaching and quota planning.
▲ −65% weekly reporting effort
ExcelDashboarding
Leads were going to the wrong reps
I built a geo-linguistic lead-distribution ruleset for a seven-member outreach team, matching prospects to language- and region-aligned reps across Africa, Asia and the Middle East.
▲ +35% first-touch response rate
Google SheetsOps design
Workforce scheduling was a manual mess
I developed a dynamic 50-slot Google Sheets workforce tracker with per-employee scheduling, leave logic, public-holiday handling and resilience to paste-format inconsistencies.
▲ ~15 hours/month of manual HR reconciliation eliminated
Google SheetsAutomation
New hires ramped slowly and mis-classified deals
I authored a printable Word SOP and onboarding playbook aligned to the company's brand standards for the 10-person sales team.
▲ −40% new-hire ramp time · −25% pipeline-stage misclassification
MS WordSOPs
Ad budget was leaking on weak creatives
After API limits on the live ad account, I built a consolidated Meta Ads performance report from raw CSV exports and isolated three underperforming creatives to pause.
▲ +22% blended ROAS the following campaign cycle
Meta AdsExcel
Support was flooded with basic questions
I designed a branded customer-facing after-sales support guide for the company's residential app, mapping post-fulfilment touchpoints and self-service flows.
▲ −30% inbound Level-1 support queries
DocumentationCX design
Jan 2025 — Apr 2026Dubai, UAE
HSI Corporate Services — Data & Marketing Analyst
Owned analytics and marketing intelligence: unifying data sources, automating data quality, and turning competitive and social insight into campaign strategy.
Tools · Python · SQL · ETL · Google Analytics · Social analytics
Five data sources that never agreed
I led the integration of five distinct sources, including CRM and website analytics, into one reporting layer for 200+ marketing campaigns.
▲ +40% data accuracy · faster, trusted reporting
PythonSQLETL
Missing values broke every report
I automated missing-value handling across multiple platforms so the analytics team stopped cleaning data by hand.
▲ −20 hours/month · +50% data-quality score
PythonAutomation
Traffic & behaviour reporting was too slow to act on
I streamlined website traffic and user-behaviour reporting so marketing could adapt strategy quickly.
▲ −60% report-generation time · +20% audience engagement
Google AnalyticsReporting
No clear read on the competition
I analysed the competitive strategies of 15 key industry players to surface trends and gaps, which became three new marketing initiatives.
▲ +40% lead generation
Competitive analysis
We were guessing at the audience
I ran market research across 5,000+ customer surveys to uncover demographics and buying behaviour.
▲ +30% targeted-marketing effectiveness
Market researchSurvey analysis
Content wasn't landing on social
I analysed social metrics across five major platforms to find the audience trends that should drive content.
I built a robust personal brand as a data & marketing expert through consistent insight-sharing and active discussion.
▲ +150% LinkedIn follower engagement in six months
Personal brandingLinkedIn
Dec 2022 — Jan 2025London, UK · Remote
Nexford University — Junior Data Analyst, Sales & Admissions
Decision support for sales and admissions: BI dashboards, KPI tracking and competitor analysis that aligned ten teams around one trusted view of the funnel.
Tools · Power BI · SQL · Excel
Sales were flat and decisions were slow
I formulated data-based recommendations and built the dashboards behind them to optimise the sales and admissions process.
▲ +46% increase in overall sales
Power BISQL
Stakeholders couldn't read the data
I developed and maintained Power BI dashboards visualising key sales metrics, turning trends into discussions and actionable strategy.
▲ Clear stakeholder comprehension driving the +46% lift
Power BIData viz
Ten teams, ten versions of the truth
I evaluated the data needs of 10 teams and delivered targeted recommendations with seamless access to the information they needed.
▲ +20% response times on key projects
RequirementsStakeholder mgmt
Strategy lacked market context
I conducted market and competitor analysis to support strategic planning.
▲ +20% market share
Market analysis
Board reports couldn't have errors
I prioritised data quality and integrity for reports used in critical business decisions, and built a milestone-tracking tool across teams.
▲ 100% report accuracy · 10 KPIs delivered on time, no added cost
Data QAKPI tracking
The product didn't reflect student needs
I analysed student-feedback data and identified three major pain points that drove product improvements.
▲ +60% user-satisfaction scores
Feedback analytics
Apr 2022 — Oct 2022Delhi, India
Wobot.ai — Data Analyst & Engineering Intern
Where it began: cross-functional analytics, BI reporting and predictive modelling, plus rigorous data-quality assurance on datasets used for strategic decisions.
Tools · Power BI · Python · Statistics
Teams worked without data-informed direction
I collaborated across interdisciplinary teams to generate insights and recommendations for business advancement.
▲ +10% project outcomes
Analytics
Stakeholders needed clearer reporting
I developed Power BI reports and visualisations that made complex data easy to act on.
▲ +18% stakeholder decision-making
Power BI
Operations had hidden inefficiencies
I applied statistical analysis and predictive modelling to find optimisation opportunities.
▲ +12% operational efficiency
PythonPredictive modelling
Lead generation was underperforming
I partnered with marketing on workflow creation and new campaigns.
▲ +40% average lead generation over 6 months
CampaignsWorkflow
Datasets weren't trustworthy enough for strategy
As an engineering intern I ran comprehensive data-quality assurance, finding and correcting discrepancies.