P
Forward Deployed Engineer
ГибридПолная занятостьSystems IntegrationEnterprise Software
Join a predictive analytics team to build and deploy customer-specific models in real-world data environments. This contractor role is based in Herzliya, Israel, works hybrid from the local office, and requires availability during US Eastern Time hours.
Обязанности
- Lead technical discovery with customers, assess their data and business processes, and set implementation expectations.
- Design data models, define prediction metrics, and map customer data sources to product requirements and best practices.
- Build and present customer-specific predictions, explaining methodology, accuracy, and activation to technical stakeholders.
- Guide customer IT and data teams through integrations; tune model parameters and resolve data quality, configuration, and expectation issues.
- Help customer teams turn predictions into actions and document repeatable playbooks for customer success, sales, and product teams.
- Enable internal champions and share customer learnings with product and engineering teams to inform the roadmap.
Требования
- At least 2 years of experience in pre-sales engineering, technical account management, or a similar customer-facing technical role in B2B SaaS.
- Hands-on SQL skills, including exploring unfamiliar schemas, building data models, and validating data quality in customer environments.
- Ability to lead technical discovery and explain complex concepts to business stakeholders and data or engineering teams.
- Ability to take ownership and make progress amid ambiguity.
- Excellent written and verbal English communication skills.
- Based in Israel, able to work hybrid from the Herzliya office, and available during US Eastern Time hours.
Будет плюсом
- Experience with data, analytics, BI, analytics engineering, data analysis, BI development, or data science.
- Experience with cloud data warehouses such as Snowflake, BigQuery, Redshift, or Azure Synapse, and CRM data structures such as Salesforce objects and renewal workflows.
- Familiarity with product analytics tools such as Pendo, Mixpanel, or Amplitude.
- Exposure to machine learning concepts such as model training, evaluation, and explainability.