Teams at 6sense

Build and operate production machine-learning systems, including training, deployment, monitoring, retraining, APIs, data pipelines, dashboards, and orchestration. Develop customer-facing workflows for model refreshes and health visibility, automate validation and rollout processes, and improve Kubernetes, CI/CD, observability, and deployment tooling. Partner with customers and internal teams to turn tailored solutions into reusable platform capabilities while ensuring reliability, rollback safety, and operational maintainability.

Leads forward-deployed data science engagements for strategic customers, tailoring predictive models to customer data and go-to-market processes. The role owns discovery, production deployment, validation, model changes, customer reviews, and measurable business outcomes. It also productizes recurring solutions, influences the predictive roadmap, establishes team standards, and mentors data scientists. Strong production machine learning, Python, SQL, customer-facing consulting, communication, and product judgment are required.

Lead customer-facing data science engagements using production CRM, marketing, firmographic, and intent data. Build, retrain, tune, validate, calibrate, and explain machine learning models for account and contact scoring. Present business impact to nontechnical customers, partner with MLOps to deploy solutions, and convert recurring insights into reusable product capabilities.