I do bespoke clustering for data sets small or big (> Tb): images, text, sound, time-series, code.
Most clustering methods break down when the data gets messy—overlapping groups, spherical clusters have too coarse resolution, unclear boundaries, weak signal. Tools like K-means assume simple shapes. Real data rarely behaves that way.
I build custom clustering solutions that work on difficult datasets, where patterns are subtle but still there. I’ve applied this across biomedical data, legal documents, IoT sensors, imaging, and behavioral data.
If your data has structure but standard methods aren’t finding it, I can help uncover it and go beyond k-means, cosine similarity and random forests.
If an initial data analysis shows there’s no meaningful signal to extract, there’s no charge.
All clustering is done bespoke, reviewed by ML scientists.
Dablam | BDR engineer | Remote or on-site in NYC or London, UK| full-time or part-time
Dablam is a reputation management company that works with top companies to shape their communication, product stories and their impact in the real world. We work with product companies, brands and campaigns for product launches.
We're looking to hire an senior developer specialized in BDR and top of the funnel outreach automation through etl pipelines, openclaw, AI agents, clay and pure software engineering. ML and data science are required as we seek to detect signal in very noisy datasets. We generate our own leads today. We seek to employ an engineer that can own the pipeline stability and the results it produces. This is an engineering role. Experience in lead-gen matters but it's not mandatory.
* 2-4 years experience in software development;
* Typescript, javascript, python, bash, linux;
* familiarity with AI agents, ML and scikit-learn;
Reach out to me directly with your CV and victor that works at dablam.co.uk.
We are hiring a DevOps to deploy and monitor an app in AWS GovCloud.
US persons from US territory only please. 5-10 years managing cloud infra / cicd / security / backups / kms / app config.
I do bespoke clustering for data sets small or big (> Tb): images, text, sound, time-series, code.
Most clustering methods break down when the data gets messy—overlapping groups, spherical clusters have too coarse resolution, unclear boundaries, weak signal. Tools like K-means assume simple shapes. Real data rarely behaves that way.
I build custom clustering solutions that work on difficult datasets, where patterns are subtle but still there. I’ve applied this across biomedical data, legal documents, IoT sensors, imaging, and behavioral data.
If your data has structure but standard methods aren’t finding it, I can help uncover it and go beyond k-means, cosine similarity and random forests.
If an initial data analysis shows there’s no meaningful signal to extract, there’s no charge. All clustering is done bespoke, reviewed by ML scientists.
Email: "v" that works at @ https://denovoclustering.com/