Data Scientist
Forward Networks is transforming how the world’s most complex networks are managed and secured. Founded in 2013 by four Stanford Ph.D.s, we 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.
Our 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.
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