Sr. Data Scientist, Forward-Deployed
About this role
Our Mission:
6sense's mission is to multiply what matters: growth, retention, and efficiency. We envision a future where companies, teams and people reach their full potential.
Our People:
People are the heart and soul of 6sense. We serve with passion and purpose. We live by our Being 6sense values of Win as One Team, Stay Curious, Do The Right Thing, Own the Outcome, and Create Belonging. Every 6sensor plays a part in defining the future of our industry-leading technology. 6sense is a place where difference-makers roll up their sleeves, take risks, act with integrity, and measure success by the value we create for our customers. We want 6sense to be the best chapter of your career.
Senior Data Scientist, Forward Deployed
Forward Deployed Engineering · Predictive track · Senior
TEAM Forward Deployed Engineering (FDE), Predictive track, in Data Science & AI Engineering
REPORTS TO Director of Data Science
LEVEL Senior (5+ years) — the team's lead modeler
LOCATION United States
THE ROLE IN ONE PARAGRAPH
We're hiring a Senior Data Scientist to be the team's lead modeler. You'll work hands-on with our strategic customers' data to tailor, retrain and validate the models that tell their sales and marketing teams which accounts and buyers to focus on.
You'll usually drive two or three customer engagements at once, each on real production data, and present the results in terms of business value. The best of your work becomes a standard capability for every 6sense customer.
What You'll Do
Build for the customer
• Get to know each customer's go-to-market and data, from CRM and marketing automation to firmographic and intent signals. • Retrain and tune account and contact models: ideal customer profile and industry definitions, keyword strategy, how CRM activity feeds the models, feature selection, and the balance of first- and third-party signals. • Prove impact with backtests against the live model and, where possible, the customer's own scoring, using opportunity conversion by score bucket. • Calibrate score thresholds and scaling so customers get a steady, explainable flow of qualified accounts. • Build customer-ready deliverables: review decks, explainability views, score files and documentation customers can verify. • Partner with the team's MLOps engineer to bring solutions into production so they keep delivering after handoff.