Staff Data Scientist, Forward Deployed

6sense; Oregon; Hybrid; USD 180.000 - 240.000; Vollzeit

Zusammenfassung

6sense seeks a Staff Data Scientist, Forward Deployed, to lead data science engagements with marquee customers. You will tailor predictive models to client go-to-market needs, stay hands-on, and drive five to ten engagements while feeding learnings back into product.

This role requires 10+ years of ML production experience, strong Python/SQL, and excellent communication with executives and engineers. You’ll collaborate with professional services to turn insights into measurable outcomes.

Qualifikationen

• 10+ years building and deploying ML models in production.
• Experience working directly with customers on their data (consulting or forward-deployed).
• Strong applied ML fundamentals: tree-based models, feature engineering, evaluation, calibration.

Aufgaben

• Lead the technical side of strategic customer engagements, from discovery to production.
• Collaborate with marketing and revenue ops to understand go-to-market goals and data needs.
• Tailor models for each client: ICP/industry, keyword/intent, CRM inputs, scoring/thresholds.
• Shape engagements with Professional Services and Customer Success: scope, plan, estimate, success measures.
• Lead reviews with customers backed by backtests and conversion analysis.
• Tell stories of work in the customer's language to business leaders and engineers.
• Guide customers through model/configuration changes for clarity.

Kenntnisse

ML production experience

Customer engagements

Applied ML fundamentals

Model changes in production

Python & SQL

Engagement management

Executive communication

Product mindset

Tools

SingleStore

Hive

Spark on AWS

Jobbeschreibung

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.

Staff Data Scientist, Forward Deployed

Forward Deployed Engineering · Predictive track · Staff TEAM Forward Deployed Engineering (FDE), Predictive track, in Data Science & AI Engineering.

REPORTS TO Head of Data Science & AI Engineering

LEVEL Staff (10+ years) — leads the team's customer engagements

LOCATION United States

THE ROLE IN ONE PARAGRAPH

Our largest customers want data scientists who work directly with their teams. As Staff Data Scientist, Forward Deployed, you'll lead that work: partnering with strategic customers to tailor our predictive models to how they go to market, and making sure the results show up in their pipeline. You'll set the technical direction for five to ten customer engagements at a time while staying hands-on, and carry what you learn back into the product. This is a high-ownership role for someone who enjoys ambiguity, likes being close to customers, and wants their work to show up both in customer results and in the product.

What You'll Do

• Lead the technical side of strategic customer engagements, from discovery to a solution running in production.
• Partner with customers' marketing and revenue operations teams to understand their go-to-market, data and goals, and find where predictive intelligence can have the most impact.
• Tailor and optimize models for each customer: ideal customer profile and industry definitions, keyword and intent strategy, how CRM and marketing automation activity feeds the models, and score thresholds.
• Shape each engagement with Professional Services and Customer Success: scope, plan, estimate and success measures.
• Lead customer reviews that recommend the next model, backed by backtests and conversion analysis customers can verify in their own data.
• Tell the story of the work in the customer's language, so results land with business leaders as well as practitioners.
• Guide customers through model and configuration changes so their teams know what to expect.

Productize for everyone

• Turn what works into reusable patterns, and bring the ones that recur across customers to Product as roadmap input backed by field evidence.
• Set the team's standards for discovery, validation, documentation and handoff, and mentor its data scientists.

What You'll Bring

• Required: 10+ years building and deploying machine learning models in production, ideally supervised models on tabular or behavioral data (propensity, scoring, ranking or similar).
• Experience working directly with customers on their data: consulting, client-site work, or a forward-deployed or solutions role at a company like Palantir or in fintech.
• Strong applied ML fundamentals, including tree-based models such as XGBoost and Random Forest: feature engineering, evaluation, calibration, threshold setting, and healthy skepticism about what a metric is telling you.
• Experience owning model changes in production end to end: backtesting, promotion decisions and rollback.
• Fluent in Python and SQL, and comfortable in messy, fragmented customer data rather than clean benchmarks.
• Able to run two or three engagements at once and switch between them without a fixed sprint plan.
• Exceptional communication: you can tell the story of the work to an executive and to an engineer.
• A product mindset: you'd rather build a capability once for every customer than solve it ten times by hand.

Nice to have: B2B go-to-market data (CRM, marketing automation, intent, ABM or predictive scoring); explaining model output to non-technical users; leading a small team or a portfolio of client engagements; building or evaluating LLM-based tools and agents; data platforms such as SingleStore, Hive or Spark on AWS.

What Success Looks Like

• In 3 months: you've led engagements end to end and delivered a measurable improvement in at least one enterprise customer's predictive results.
• In 6 months: patterns from your engagements are on the predictive roadmap, and at least one tailored solution is on its way to becoming a standard product capability.