{"version":"0.1","company":{"name":"YubHub","url":"https://yubhub.co","jobsUrl":"https://yubhub.co/jobs/title/commercial-data-scientist"},"x-facet":{"type":"title","slug":"commercial-data-scientist","display":"Commercial Data Scientist","count":1},"x-feed-size-limit":100,"x-feed-sort":"enriched_at desc","x-feed-notice":"This feed contains at most 100 jobs (the most recently enriched). For the full corpus, use the paginated /stats/by-facet endpoint or /search.","x-generator":"yubhub-xml-generator","x-rights":"Free to redistribute with attribution: \"Data by YubHub (https://yubhub.co)\"","x-schema":"Each entry in `jobs` follows https://schema.org/JobPosting. YubHub-native raw fields carry `x-` prefix.","jobs":[{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_efb680ee-b84"},"title":"Commercial Data Scientist","description":"<p>Synthesia is hiring a Commercial Data Scientist to build, deploy, and maintain data science models that directly improve revenue outcomes and customer experience.</p>\n<p>You&#39;ll work end-to-end: from defining the problem with commercial stakeholders, to building and validating models, to deploying and running them reliably in production with the Data Engineering team.</p>\n<p>Typical projects include customer health scores, lead intent scoring, churn/expansion predictors, segmentation, and experimentation frameworks that make those models actionable.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Partner with Sales, RevOps, CS and Marketing to translate ambiguous commercial questions into measurable problems and model-ready datasets.</li>\n<li>Build and iterate on predictive and classification models (e.g., health scoring, intent scoring), with rigorous validation, monitoring, and clear success metrics.</li>\n<li>Deploy models into production in collaboration with Data Engineering (batch jobs, pipelines, feature generation, versioning, and observability).</li>\n<li>Maintain and improve existing models: performance monitoring, retraining strategies, drift detection, and reliability.</li>\n<li>Make models usable: deliver clear outputs, documentation, and guidance so commercial teams can act on insights.</li>\n<li>Contribute to a strong DS craft culture: code quality, reproducibility, experimentation discipline, and pragmatic model selection.</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>Several years of industry experience as a Data Scientist (or similar), building statistical/ML models end-to-end.</li>\n<li>Strong foundations in applied machine learning and statistics, with good judgment about model complexity vs. impact.</li>\n<li>Production mindset: you&#39;ve worked with deployed models, and understand monitoring, retraining, data quality, and operational constraints.</li>\n<li>Strong SQL and Python skills, with experience in data wrangling and feature engineering.</li>\n<li>Ability to communicate clearly with technical and non-technical partners, including explaining trade-offs and model limitations.</li>\n<li>Comfort operating in a high-autonomy environment: you can plan your work, drive alignment, and ship without being handed tickets.</li>\n</ul>\n<p><strong>Nice-to-Haves</strong></p>\n<ul>\n<li>Experience working on commercial / go-to-market problems (rev intelligence, lead scoring, churn, expansion, attribution, forecasting).</li>\n<li>Experience working closely with modern data stacks (Snowflake, dbt, Airflow) and production ML patterns.</li>\n<li>Experience designing model outputs that integrate cleanly into commercial workflows (dashboards, alerts, CRM signals).</li>\n</ul>\n<p><strong>How We Work</strong></p>\n<p>We optimize for responsibility and freedom.</p>\n<p>That means:</p>\n<ul>\n<li>No Jira, no ticket conveyor belt , we run on ownership and a small number of high-impact projects.</li>\n<li>Close collaboration with commercial stakeholders and Data Engineering to ship real outcomes.</li>\n<li>A bias toward pragmatic solutions that can be deployed, monitored, and improved.</li>\n</ul>\n<p><strong>Why Join</strong></p>\n<ul>\n<li>Work on problems that sit at the intersection of product usage and commercial outcomes.</li>\n<li>Own impactful, end-to-end projects , from definition to production.</li>\n<li>Join a team that values autonomy, craft, and speed.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_efb680ee-b84","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Synthesia","sameAs":"https://synthesia.ai/","logo":"https://logos.yubhub.co/synthesia.ai.png"},"x-apply-url":"https://jobs.ashbyhq.com/synthesia/a40cbbc3-6be7-48a2-b8c7-1f09a1c5aa43","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"Full time","x-salary-range":null,"x-skills-required":["Python","SQL","Machine Learning","Statistics","Data Wrangling","Feature Engineering"],"x-skills-preferred":[],"datePosted":"2026-04-24T13:16:17.659Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Europe"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, SQL, Machine Learning, Statistics, Data Wrangling, Feature Engineering"}]}