Forward Networks seeks a pragmatic, end-to-end Data Scientist who can operate across the full data lifecycle, from ingestion and modeling to productionizing key data systems. This is a high-impact, high-agency, "help steer the ship" role which reports directly to the CTO. Modern AI-assisted development tools make this role possible, where the data scientist can now do real engineering, too. What You'll Do - Collaborate closely with other teams (Sales, Finance, Product, Marketing, and more) to translate problems and needs into action-oriented data solutions - Design, build, and maintain data pipelines for reliable ingestion and transformation - Rapidly prototype and iterate using AI coding tools to accelerate development and reduce toil - Drive rigor and best practices, with a focus on data quality, consistency, and transparency - Develop and deploy statistical models and machine learning, where appropriate - Build clear, decision-oriented visualizations and dashboards for stakeholders across multiple departments - Own selected production data systems: selection, orchestration, monitoring, and tuning - Communicate and shepherd key data results and analysis to executives What We're Looking for - Experience with B2B SaaS-relevant data, including Salesforce and financial metrics - Strong communication skills and ability to work effectively across multiple departments and stakeholder groups - Ownership mindset and ability to deliver end-to-end outcomes independently; must be a "startup type" - Demonstrated ability to design data pipelines and work with imperfect, evolving data sources - Sharp attention to data quality, including validation, anomaly detection, and root-cause analysis of inconsistencies - Strong proficiency in Python and SQL; experience with modern data stack tools (e.g., dbt, Airflow, Spark, or equivalents, a plus) - Experience with data visualization tools (e.g., Tableau, Looker, or similar) - Some familiarity with infrastructure and related setup (databases, data warehouses, VMs) - Knowledge of core machine learning concepts and when to apply them pragmatically Example Initial Projects - Build a likelihood-of-close model for Salesforce opportunities, which factors in relevant metadata and history - Create a framework and initial implementation for an executive operational dashboard, working with a broad set of teams - Define, validate, and implement key SaaS product-usage metrics As we grow, you will, too, with the broad scope of a software startup. Location: Bay Area preferred (HQ in Santa Clara), but open to the right remote candidate. Salary Range: The base pay range for this role is between $170,000 and $190,000. Base pay will depend on your skills, qualifications, experience, and location