Hi, I'm Rasmus Kampmann
Data Analyst | BI Specialist | Power BI Developer
- Power BI
- SQL
- Python
- AI workflows
I turn scattered commercial data into systems you can trust.
3+ years working in commercial, now building the Power BI reporting, forecasting, and data models behind commercial decisions, in agriculture and beyond.
What I Do
The tools I use most, grouped by what I actually use them for.
Power BI
I build dashboards leadership actually uses. Built around the decisions teams need to make, so reporting drives action instead of just showing numbers.
SQL
I build the data layer that everything else runs on. Joins, transformations, and pipelines that turn raw data into analysis-ready tables your team can trust.
Excel
I run the financial modelling in Excel where it belongs. Forecasts, budgets, margin and customer profitability, and KPI definitions that hold across sales, operations, and production, modelled in the tool the business already uses.
Python
I build the automation, models, and analytical work spreadsheets can't handle. From data pipelines to ML classifiers to deeper analysis at scale.
AI workflows
I use AI where it removes manual reporting work. Automating data prep, enrichment, and the repetitive parts of analysis, built into the pipeline rather than added afterward. A tool in the stack, not the headline.
Web scraping
I pull external signals into the same warehouse as internal data. Weather and market data, prices, and outside context that planning and forecasts depend on, so decisions account for what's happening outside the business, not just inside it.
My Projects
Production systems behind reporting, forecasting, and commercial decisions. Written for non-technical readers.
Invoice & Financial Dashboard
One trusted view of profit per product, profit per customer, and the cash owed, built from invoices and reconciled to the accounts within 1.25%. Commercial figures below are illustrative; the reconciliation is real.
Operations & Production Planning
A live system that tells a seed business what to produce, how much, and when. It reproduces the planner's own numbers exactly, validated against their spreadsheet. A planning system with scenario testing, not a forecast.
Software Detection ML Model
Reorders the cold-outbound dialler queue around the companies most likely to fit, before reps make a single call. Predicts accounting-software adoption from public Danish company-registry data alone, no paid data vendor.
Funnel & Segment Analysis
Funnel decomposition and firmographic segment-lift analysis across 102,007 records. One employee band converted at 37.5%, everyone else at 3.0%. The drop was after the first conversation, not before it. Synthetic data, real method.
Agentic External Intelligence Platform
Personalised research, competitor monitoring, and weekly briefings replaced manual work for a B2B agriculture company. Live RAG dashboard, multi-LLM interpretation, cross-source signal detection, 228 sources.
Channel & Churn Analysis
Multi-factor scoring and twelve-month survival analysis across ten channels reported as one blended mix. Scored on win rate, capacity, speed, and churn. Synthetic data, real method.
About Me
Hi, I'm Rasmus. I turn scattered commercial data into systems you can trust.
I build the business intelligence, reporting, and financial analysis that turn scattered commercial and operational data into decisions leadership can act on.
My background is in commercial operations, across sales, marketing, finance, and the day-to-day of running a business. That's what sets the work apart: I read the numbers from inside the business, so I know what they mean, where reporting breaks, and how sales, finance, and operations actually use them, because I've worked in those functions, not just reported on them.
At Veginova, an agricultural seed business, I'm building the operating system behind the data, BI, and reporting the business runs on. It builds on the BI and reporting stack I already own here, now extended into the financial and operational layer: forecasting, reporting, and the analysis leadership makes decisions on. The work cut reporting time by 10+ hours a week and lifted KPI accuracy by 40%+.
How I work:
- Build clean, consistent data structures as the foundation
- Automate ingestion and transformation instead of rebuilding manually
- Keep pipelines lightweight, not over-engineered
- Build Power BI models that are easy to maintain and extend
- Build dashboards around the decisions leadership makes
- Use AI where it makes the work faster or more accurate
Stack: SQL, Python, Power BI, Excel, data modeling, ETL, web scraping, AI workflows. Hands-on across ERPs, CRMs, and spreadsheet/BI tools: the full commercial data layer.
On the AI side: I use AI to automate reporting and analysis, scrape and structure commercial data, and build agentic systems that surface information without manual work, using Claude Code, n8n, Python ML, RAG, and multi-LLM workflows.
I replace manual spreadsheets and disconnected reporting with systems that run on their own and make the business easier to understand. The outcome teams hire me for: stop rebuilding reports every Monday, stop questioning the numbers, start making commercial decisions from data you trust.
Open to data, BI, and Power BI developer roles in Denmark.
Previous Experience
Roles where I built the data systems, dashboards, and automation behind real commercial decisions.
Feb 2026 – May 2026 · Full-time · Hybrid
Data Analyst & Commercial Analytics
Digi-Tal Regnskab
- Owned the data work behind a Danish SMB accounting and fintech firm: ICP, scoring, software detection, and full-channel revenue analysis, from raw source through to operationalised scores feeding sales.
- Built ICP and predictive lead-scoring models (strong holdout) plus an ML classifier identifying a prospect's accounting software (~75% accuracy across the Danish SMB market) from Playwright scraping and enrichment waterfalls.
- Full-channel revenue analysis across Meta, Google, LinkedIn outbound, cold calling, and inbound: close rate, conversion, meeting time, and pipeline velocity by channel and segment. Identified which channels drove customers and which burned budget.
- Customer, churn, and attribution analysis: segmented the network into customer, lead, lost, and inactive, and built a full-funnel attribution model joining campaign data, CRM deals, and the Danish business registry to isolate the signals separating payers from non-converters.
- Rebuilt the sales commission model with forecasting weightings, shifting payouts toward subscription and MRR so sellers optimised for LTV instead of discounting to close. Operationalised the scores through an end-to-end LinkedIn pipeline (scraping, enrichment, scoring, sequencing).
Stack: SQL · Python · Pipedrive · Clay · Playwright · Apify · HeyReach · Claude
May 2025 – Feb 2026 · Full-time · Hybrid
Data Analyst & BI Specialist
Veginova Seeds
- Owned the BI and reporting stack across sales, operations, and production. Built the finance source of truth, now extending to operations and forecasting.
- Improved KPI accuracy by 40%+. Standardised metric definitions across teams.
- Cut reporting time by 10+ hours per week. Stabilised broken reporting workflows and consolidated data sources.
- Resolved data inconsistencies across inventory, sales, and production systems.
Stack: SQL · Power BI · Python · Excel · Clay · Claude Code
Aug 2023 – May 2025 · Full-time · Hybrid
Marketing Specialist & RevOps
Veginova Seeds
- B2B marketing and RevOps in agriculture, working with international wholesale, distributor, and grower customers.
- Outbound lead sourcing, CRM hygiene, and lead scoring and prioritisation.
- Trade-fair and grower-event sourcing, pipeline reporting, and channel attribution.
Jun 2024 – Aug 2025 · Self-employed · Remote
Founder · Data & RevOps
Sira Logic
- Service business building AI-driven lead generation, enrichment, and CRM automation for B2B companies.
- Built lead enrichment and scoring workflows. Qualification accuracy improved by 30–40%.
- Built CRM automation pipelines integrating HubSpot and GoHighLevel with external data sources.
- Built custom web scraping systems for industry-specific data sources.
Stack: SQL · Python · Clay · Apify · HubSpot · GoHighLevel · HeyReach
Jan 2025 – Jan 2026 · Freelance · Remote
AI & LLM Data Analyst
Outlier
- Reviewed and annotated 1,000+ Danish-language AI conversations to improve response quality.
- Spotted patterns where models failed and fed that back into training data.
- Built practical understanding of how LLMs work and where they break. The same insight powers the AI scoring and qualification workflows I build today.
Jan 2023 – Aug 2023 · Part-time · Hybrid
Marketing & Digital Graduate
Damstahl Danmark
- Managed product and marketing data in ERP and CRM platforms across European markets.
- Built Excel dashboards for campaign reporting.
- Standardised regional data processes.
See my freelance services
View Services →Recruiters: see my LinkedIn or grab my CV in English or Danish.