Data Scientist

Forward Networks • Santa Clara, CA

6d • Hybrid

About The Position

Forward Networks is transforming how the world’s most complex networks are managed and secured. Founded in 2013 by four Stanford Ph.D.s, the company built the industry’s first network digital twin — a mathematically precise model of the production network that gives IT teams unmatched visibility, verification, and agility across every major cloud and vendor environment. Their customers include global leaders such as Goldman Sachs, PayPal, S&P Global, IBM, and Dell, as well as fast-growing enterprises and government agencies. According to IDC, Forward Networks customers realize an average of $14.2 million in annual benefits through improved efficiency and security. Backed by world-class investors including Andreessen Horowitz, Goldman Sachs, MSD Partners, and Threshold Ventures, Forward Networks offers a people-centric, innovative culture where brilliant minds are shaping the future of network reliability, security, and AI-ready operations. 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.

Requirements

• 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 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

Nice To Haves

• Experience with modern data stack tools (e.g., dbt, Airflow, Spark, or equivalents, a plus)

Responsibilities

• 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 This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed
• Number of Employees: 101-250 employees