Merck
Circuit mix
Where Merck shows up, by circuit. Each event counts once: 2 if it sponsored, 1 if it only had speakers. Hover a segment for the conference.
- Enterprise, analyst & AI expos43%10 events
- Python & R data science26%4 events
- Cloud providers17%4 events
- Vendor flagships & roadshows9%2 events
- Modern data stack & practitioner4%1 event
Presence by conference and year
Each cell is one conference in one year. Fill shows the company sponsored, shaded by its best tier that year; a dot means it had speakers there. Hover for details; click to open the event.
- Title
- Platinum
- Gold
- Silver
- Bronze
- Other / unlabeled tier
- Had speakers
Activity by year
Three measures on one year axis; each panel has its own scale. 2027, 2028 is still mostly ahead, so its bars are faded and incomplete.
Conferences present at
Distinct conferences each year, split by whether the company sponsored or only had speakers there.
- Sponsored
- Speakers only
Distinct speakers
People from this company on a program that year, each counted once.
Sponsorships by tier
Sponsorship rows per year (one per event and listing), stacked by normalized tier.
- Title
Where they've grown or pulled back
FlatSponsored 1 conference in 2026, flat from 1 in 2025.
Counted per conference. 2026 is the latest year whose conferences have mostly happened. Tiers use the best tier each year; swatches show the path, oldest first. A conference counts as pulled out only when a later event published a complete sponsor list, since most events don’t say whether their list is complete.
Lookalikes
Companies with the most similar conference footprint: they sponsor and speak at the same conferences. Bars are cosine similarity, from 0 (nothing shared) to 1 (identical).
- Pearson0.84
- Spare Cores0.82
- E.ON0.76
- Schneider Electric0.76
- Flatiron Health0.75
- Moderna0.74
- ASAPP0.73
- GetYourGuide0.73
8 Cluster: PyData · posit::conf circuit →
Often sponsors alongside
Companies that sponsored the same events, by number of shared events (out of 2 this company sponsored).
| Company | Shared events | Share |
|---|---|---|
| appliedAI Institute for Europe gGmbH | 2 | 100% |
| Bausparkasse Schwäbisch Hall AG | 2 | 100% |
| Cologne Intelligence | 2 | 100% |
| DeepL | 2 | 100% |
| DjangoGirls | 2 | 100% |
| EuroPython Society | 2 | 100% |
| Gurobi | 2 | 100% |
| Hessian AI | 2 | 100% |
| inovex GmbH | 2 | 100% |
| Lidl Stiftung & Co. KG | 2 | 100% |
| NumFOCUS | 2 | 100% |
| Pioneers Hub | 2 | 100% |
| Probably Private | 2 | 100% |
| PyData Berlin | 2 | 100% |
| PyLadies | 2 | 100% |
Neighborhood: companies with nearby conference footprints
Merck (ringed) and the 30 companies closest to it on the company map. Close together means they sponsor and speak at many of the same conferences. Distances are only meaningful locally; the axes have no meaning. Dot size: conferences present at. Color: cluster.
Sponsorships 2
| Event | Date | Place | Tier as listed | Normalized tier |
|---|---|---|---|---|
| PyCon DE & PyData 2026 | Apr 14–16, 2026 | Darmstadt, Germany | Keystone | Title |
| PyCon DE & PyData 2025 | Apr 23–25, 2025 | Darmstadt, Germany | Keystone | Title |
Speakers 39
| Speaker | Event | Role | Talk | Links |
|---|---|---|---|---|
| Loris Gordon Giaimi | DACH AI, Data Analytics & Insights Summit 2026 | speaker | — | — |
| Geoffrey Lobo | Open House Roadshow Bangalore 2026 | speaker | Customer Story: How Merck uses Langfuse | — |
| Harsha Gurulingappa | Open House Roadshow Bangalore 2026 | speaker | Customer Story: How Merck uses Langfuse | — |
| Nicolas Renkamp | DuckCon #7 | talk | SQLFrame migrates PySpark to DuckDB without code changes | — |
| Harsh Singh | AI and Data in Pharma & Healthcare Summit 2026 Boston | speaker | — | — |
| Ronojit Adyanthaya | AI and Data in Pharma & Healthcare Summit 2026 Boston | speaker | — | — |
| Ofure Akhibi Obazee | AI and Data in Pharma & Healthcare Summit 2026 | speaker | — | — |
| Andreas Wurl | PyCon DE & PyData 2026 | talk | Octopus AutoML: Extracting Signal from Small and High-Dimensional Data | — |
| Bernhard Schäfer | PyCon DE & PyData 2026 | talk | Empowering Data Scientists with Zero Platform Friction: Deploying Streamlit & Friends in 3 Minutes | — |
| Nils Haase | PyCon DE & PyData 2026 | talk | Octopus AutoML: Extracting Signal from Small and High-Dimensional Data | — |
| Yuan Qin | AWS re:Invent 2025 | chalk talk | Quantum Computing: Accelerating Pharma Innovation | — |
| Alexander Pilipas | DACH AI, Data Analytics and Insights Summit 2025 | speaker | — | — |
| Julie Fang | EuroPython 2025 | talk | Transforming Data Interaction: A Self-Served Insight Tool with LangGraph | Video |
| Karol Herta | Data in Manufacturing & Smart Industry Summit DACH 2025 | speaker | — | — |
| Hrvoje Mohorić | AI and Data in Pharma & Healthcare Summit 2025 | speaker | — | — |
| Juergen Scheuenpflug | AI and Data in Pharma & Healthcare Summit 2025 | speaker | — | — |
| Adrian Šošić | PyCon DE & PyData 2025 | sponsor | BayBE: A Bayesian Back End for Experimental Planning in the Low-To-No-Data Regime | — |
| Alexander Hopp | PyCon DE & PyData 2025 | sponsor | BayBE: A Bayesian Back End for Experimental Planning in the Low-To-No-Data Regime | — |
| Bernhard Schäfer | PyCon DE & PyData 2025 | talk | Lessons learned in bringing a RAG chatbot with access to 50k+ diverse documents to production | — |
| Martin Fitzner | PyCon DE & PyData 2025 | sponsor | BayBE: A Bayesian Back End for Experimental Planning in the Low-To-No-Data Regime | — |
| Nico Mohr | PyCon DE & PyData 2025 | talk | Lessons learned in bringing a RAG chatbot with access to 50k+ diverse documents to production | — |
| Harsha Gurukar | AWS re:Invent 2024 | breakout | Drive innovation and results with high performance computing on AWS | Video |
| Jeff Feist | AWS re:Invent 2024 | breakout | AWS wherever you need it: From the cloud to the edge | Video |
| Matthew Studney | AWS re:Invent 2024 | innovation talk | Accelerating healthcare & life sciences innovation with generative AI | — |
| Matthew Studney | AWS re:Invent 2024 | breakout | How Merck improves drug design with biological foundation models | Video |
| Sean Finnerty | AWS re:Invent 2024 | lightning talk | Cloud transformation: Merck’s proven modernization factory model (sponsored by HCLTech) | Video |
| Vladimir Turzhitsky | AWS re:Invent 2024 | breakout | Merck advances healthcare data extraction using text-to-SQL on AWS | Video |
| Vasant Marur | posit::conf(2024) | speaker | Quality Control to avoid GIGO in Deep Learning Models | Video |
| Mariana Hebborn | AI and Data in Pharma & Healthcare Summit 2024 | speaker | — | — |
| Loris Gordon Giaimis | Ai, Data Analytics & Insights Summit DACH 2023 | speaker | — | — |
| Aman Khan | AI and Data in Pharma & Healthcare Summit 2023 | speaker | — | — |
| Fran Geatens | AWS re:Invent 2022 | breakout | Demonstrating the real enterprise value of cloud at Merck (sponsored by Accenture) | Slides · Video |
| Jeffrey Feist | AWS re:Invent 2022 | lightning talk | Experience cloud transformation and continuous modernization with HCL (sponsored by HCL Technologies) | Slides · Video |
| Ron Kim | AWS re:Invent 2022 | breakout | Demonstrating the real enterprise value of cloud at Merck (sponsored by Accenture) | Slides · Video |
| Sean Finnerty | AWS re:Invent 2022 | breakout | Demonstrating the real enterprise value of cloud at Merck (sponsored by Accenture) | Slides · Video |
| Stefanie Babka | Ai, Data Analytics & Insights Summit DACH 2022 | speaker | — | — |
| Vikas Patel | AWS re:Invent 2019 | breakout | Merck drives innovation with a “real-world data exchange” on AWS | Slides · Video |
| Alexander Kerwien | Neo4j GraphTour Berlin 2019 | speaker | Case Study Merck | — |
| Lisa Löffler | Neo4j GraphTour Berlin 2019 | speaker | Case Study Merck | — |