Staff Data Scientist, Forward Deployed
About The Position
The Staff Data Scientist, Forward Deployed, leads technical work for strategic customer engagements, partnering directly with customer teams to tailor predictive models to their go-to-market needs and improve pipeline results. The role sets technical direction across multiple engagements while remaining hands-on, and brings learnings from customer work back into the product. The position works with customer marketing and revenue operations teams to understand their data, goals, and go-to-market strategies; adapts and optimizes predictive models; and guides engagements from discovery through production. It also turns recurring customer solutions into reusable patterns and product roadmap input, establishes team standards, and mentors data scientists.
Requirements
- 10+ years building and deploying machine learning models in production, ideally supervised models on tabular or behavioral data such as propensity, scoring, or ranking.
- Experience working directly with customers on their data through consulting, client-site work, or a forward-deployed or solutions role.
- Strong applied machine learning fundamentals, including tree-based models such as XGBoost and Random Forest, feature engineering, evaluation, calibration, threshold setting, and critical interpretation of metrics.
- Experience owning production model changes end to end, including backtesting, promotion decisions, and rollback.
- Fluency in Python and SQL.
- Comfort working with messy, fragmented customer data rather than only clean benchmarks.
- Ability to run multiple engagements concurrently and switch between them without a fixed sprint plan.
- Exceptional communication skills, including explaining work to executives and engineers.
- A product mindset, with a preference for building capabilities reusable across customers rather than repeatedly solving the same problem by hand.
Nice To Haves
- Experience with B2B go-to-market data, such as CRM, marketing automation, intent, ABM, or predictive scoring.
- Experience explaining model output to non-technical users.
- Experience leading a small team or a portfolio of client engagements.
- Experience building or evaluating LLM-based tools and agents.
- Experience with data platforms such as SingleStore, Hive, or Spark on AWS.
Responsibilities
- Lead the technical side of strategic customer engagements from discovery through production deployment.
- Partner with customer marketing and revenue operations teams to understand their go-to-market strategies, data, and goals, and identify opportunities for predictive intelligence.
- Tailor and optimize customer models, including ideal customer profiles, industry definitions, keyword and intent strategies, CRM and marketing automation activity inputs, and score thresholds.
- Shape engagement scope, plans, estimates, and success measures with Professional Services and Customer Success.
- Lead customer reviews recommending next models, supported by backtests and conversion analyses that customers can verify using their own data.
- Communicate the work and its results in language appropriate for business leaders and practitioners.
- Guide customers through model and configuration changes and explain their expected effects.
- Turn successful approaches into reusable patterns and provide recurring patterns to Product as roadmap input backed by field evidence.
- Set team standards for discovery, validation, documentation, and handoff.
- Mentor the team's data scientists.
Benefits
- Health coverage and generous health insurance coverage.
- Paid parental leave.
- Generous paid time off (PTO) and paid holidays.
- Quarterly self-care days off and wellness days.
- Stock options, subject to board approval as applicable.
- Life insurance and disability insurance.
- 401(k) employer matching program.
- Learning and development initiatives, including access to LinkedIn Learning.
- Wellness education sessions and employee resource group events.
- Equipment and support for working and connecting with teams at home or in company offices.
- A bonus program or commission plan may be included as additional compensation.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
