> Markdown version of [/jobs/ext/4689254-senior-data-scientist](https://www.wearedevelopers.com/jobs/ext/4689254-senior-data-scientist). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Scientist - **Company:** DataTech Analytics - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $75,000 - **Contract:** Permanent contract - **Skills:** Data Analysis, Customer Data Management, Data Cleansing, Python (Programming Language), Raw Data, SQL Databases, Transaction Data, Feature Engineering, Model Validation - **Published:** November 12, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/pyvwcr9yco ## About the Role * Strong hands-on Python and SQL experience, with a track record of developing and implementing predictive models. * Practical experience working directly with first-party customer and transactional data. * Proven experience designing customer segmentation approaches, including selecting methodologies, validating results and supporting their application. * Experience developing propensity, churn, customer lifetime value or similar predictive models. * An understanding of how customer scores and segments are activated through marketing campaigns, CRM or retention initiatives. * Experience taking models beyond experimentation into production environments, including monitoring and ongoing improvement. * Strong statistical knowledge, analytical thinking and the ability to explain modelling decisions and trade-offs. * Confidence working independently, managing priorities and taking ownership of technical delivery. * Experience within retail, financial services, insurance, subscription businesses or other customer-focused environments would be advantageous. Consultancy or client-facing experience would also be useful. * Experience of personally developing and implementing predictive models, with the ability to demonstrate how they were applied and the commercial impact achieved. This role would suit a hands-on Senior Data Scientist who enjoys owning projects end to end, solving commercial challenges and seeing their models make a real impact on customer and marketing decisions. Applicants must have unrestricted UK right to work without employer sponsorship. This vacancy cannot accommodate Graduate/Post Study or Skilled Worker visa arrangements. ## Description Are you a hands-on Data Scientist who has developed customer segmentation, propensity or churn models that have genuinely influenced marketing activity? Can you demonstrate how your models have been used to improve customer engagement, retention or commercial performance?, An established analytics and technology business is looking for a Senior Data Scientist to develop and deliver predictive solutions using first-party customer data. You'll work across existing products and new developments, helping well-known brands understand customer behaviour, identify opportunities and make more informed decisions. This is an opportunity for someone who enjoys the full modelling lifecycle, from exploring raw data and developing models through to deployment, monitoring and measuring business outcomes. What you'll be doing: * Design and develop customer segmentation models using behavioural, transactional and demographic data. * Build and evaluate predictive models covering propensity, churn, customer value and forecasting. * Work with large-scale customer datasets, undertaking data preparation, feature engineering, statistical analysis and model validation. * Collaborate with marketing, CRM and commercial teams to translate model outputs into targeted customer activity. * Support the deployment of models into production, monitoring performance and refining approaches over time. * Work closely with engineers, product teams and stakeholders to ensure solutions are practical, scalable and commercially relevant. * Communicate modelling approaches, findings and recommendations to technical and non-technical audiences.