Data Analyst and Project Manager with good client service.
Data Analyst and Project Manager with good client service.
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Product & Service Designer- Senior Architect
- $1k+
- Earned
- 1x
- Hired
- 5.0
- Rating
- 3
- Followers
Product & Service Designer- Senior Architect
I build growth engines, not campaigns.
I build growth engines, not campaigns.
Result: Tripled inbound MQLs. Improved conversion at every funnel stage.
Before: Growth was slow. Standard instinct said: spend more on acquisition. The data said otherwise.
What I did: Ran a reverse funnel calculation that showed the real constraint was conversion rate, not top-of-funnel volume. Extra ad spend would have amplified a leaky funnel. Rebuilt the value proposition and product positioning. Overhauled the website on HubSpot CMS with redesigned information architecture, full SEO build, and conversion-focused UX. Rebuilt CRM automation: nurturing sequences, lifecycle stages, automated qualification logic.
After: x3 inbound MQLs. Conversion improved at every stage. Structural growth, not campaign-driven.
The rebranding was later validated by Marion Lemoine, Team Lead CSM at HubSpot: "The rebranding was seamless, customer-focused, and impactful. I'm sure this will bring a lot of new leads to the company."
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Result: 40x content throughput. Zero additional headcount.
Before: Property Filter produced one member success story per month, maximum. Every step was manual: interview, writing, editing brief, blog article, social copy. Short-form video: zero. SEO-optimised articles: zero.
What I built: A multi-stage AI production system using Claude. One coordinator types a single command after each member interview. The system generates: a timestamped video editing blueprint for the editor; a full SEO and GEO-optimised blog article using a validated canonical template; a publishing checklist for the web team; platform-specific social copy for 4-5 short-form clips. HubSpot MCP pulls the member's data in automatically. Automated Slack messages route each output to the right person in the right channel.
Not automation replacing humans. An intelligence layer that makes every person in the pipeline perform at a higher level.
After: 10+ stories per week. 4-5 short-form clips per story (previously zero). Substantially better video quality because editing briefs are precise and timestamped. Zero additional headcount.
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Result: 50 webinar attendees (MQLs)/week and 60 demo requests/week on autopilot. Everything built from zero.
Before: Zero evergreen digital acquisition. Every lead came from an active campaign.
What I built in 6 months: SEO engine: 6 topic clusters, 60-article editorial calendar, 5 pillar pages. Full architecture designed and deployed in 2 weeks. Paid media: evergreen system across Meta and Google (not campaign management). 32-script ad creative library. 50+ published customer UGC videos. 20+ customer studies articles optimised for SEO GEO. A/B/C test iterations on emails, forms, landing pages, CTAs. HubSpot: custom pipeline stages, full multi-channel attribution, automated lifecycle workflows from first touch to onboarding without human intervention. Canva brand system: 1 brand kit, 200+ assets, 15+ templates, team trained to produce on-brand content independently. Webinar infrastructure: 1,500 registrations, 600 live attendees, 40% show rate.
After: 50 webinar attendees (MQLs) per week and 60 demo requests per week, arriving without active management.
Counter-cyclical context: UK buyer demand fell 13% and proptech funding hit an 8-year low during this period.
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Property Investor Blueprint Challenge
Result: 1,500 registrations. 600 live attendees. 40% show rate.
Before: Property Filter needed a flagship lead generation event. There was no event infrastructure, no creative system, and no automation to handle registrations at scale.
What I built: Co-Designed with the founders and executed the Property Investor Blueprint Challenge end-to-end. Topic strategy first: identified the highest-anxiety question in the target audience and structured a live challenge format around solving it.
Drove registrations via paid media across Meta and Google using a creative library developed for the broader campaign.
Built full HubSpot automation: confirmation sequences, multi-touch reminder flows, post-event lead nurture routed by attendance behaviour.
All creative assets designed and produced in Canva using the brand system I built.
After: 1,500 registrations. 600 live attendees that stayed for 3 days. 40% show rate, well above industry average for B2B webinars. The event became a repeatable acquisition and sales channel, not a one-off.
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SEO Specialist - Turning Clicks Into Revenue
Analista de Datos | Insights, modelos | optimización | ML
Analista de Datos | Insights, modelos | optimización | ML
Built a centralized investment analytics and business intelligence platform to automate KPI tracking, operational reporting and executive dashboards.
The solution integrated multiple data sources into a single decision support system, eliminating manual reporting while providing daily insights into investments, clients, providers and overall business performance.
The platform included automated data pipelines, KPI monitoring and executive dashboards designed to support faster and more informed business decisions.
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Multi-Horizon Demand Forecasting
Designed and implemented a multi-horizon demand forecasting system for an e-commerce business to improve inventory planning and operational decision-making.
The solution generated forecasts across multiple planning horizons while automating forecasting workflows and scenario analysis.
This enabled business teams to make more informed purchasing and inventory decisions while reducing manual forecasting efforts.
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Credit Risk Modeling
Developed a machine learning solution for consumer credit risk assessment, helping improve lending decisions through predictive analytics.
The project included feature engineering, model evaluation and probability calibration to deliver reliable risk predictions while supporting regulatory and business requirements.
The final solution provided a scalable analytical framework for consistent and data-driven credit decision making.
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53
Designed an AI-powered decision support system combining quantitative models, machine learning and deep learning techniques to analyze financial markets.
The platform automated data collection, strategy evaluation and backtesting, providing a scalable framework for continuous strategy development.
The project demonstrated how advanced analytics can support systematic and data-driven investment decisions.:
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