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
Build for the customer
- 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.
- In 12 months: engagements move faster because of the tooling and playbook you built, and more of what customers need comes in the product out of the box.
Why this role is different: most data science roles build models at a distance from the customer or advise without shipping. This one leads the work end to end, from the customer conversation to the model in production, and turns it into product.
Base Salary Range: $194,736.75 - $265,613.90. The base salary range represents the anticipated low and high end of the base salary range for this position. Actual salaries may vary and may be above or below the range based on various factors, including but not limited to work location and experience. The base salary is one component of 6sense’s total compensation package for this position. Other compensation may include a bonus program or commission plan, and stock options if approved by 6sense’s board. In addition, 6sense provides a variety of benefits, including generous health insurance coverage, life, and disability insurance, a 401K employer matching program, paid holidays, self-care days, and paid time off (PTO). #Li-remote
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Our Benefits:
Full-time employees can take advantage of health coverage, paid parental leave, generous paid time-off and holidays, quarterly self-care days off, and stock options. We’ll make sure you have the equipment and support you need to work and connect with your teams, at home or in one of our offices.
We have a growth mindset culture that is represented in all that we do, from onboarding through to numerous learning and development initiatives including access to our LinkedIn Learning platform. Employee well-being is also top of mind for us. We host quarterly wellness education sessions to encourage self care and personal growth. From wellness days to ERG-hosted events, we celebrate and energize all 6sense employees and their backgrounds.
Equal Opportunity Employer:
6sense is an Equal Employment Opportunity and Affirmative Action Employers. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status. If you require reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please direct your inquiries to [email protected].
We are aware of recruiting impersonation attempts that are not affiliated with 6sense in any way. All email communications from 6sense will originate from the @6sense.com domain. We will not initially contact you via text message and will never request payments. If you are uncertain whether you have been contacted by an official 6sense employee, reach out to jobs@6sense.com
Skills Required
- 10+ years building and deploying machine learning models in production, preferably supervised models using tabular or behavioral data
- Direct customer experience working with customer data, such as consulting, client-site work, forward-deployed, or solutions experience
- Strong applied machine learning fundamentals, including feature engineering, evaluation, calibration, threshold setting, XGBoost, and Random Forest
- Experience owning production model changes end to end, including backtesting, promotion decisions, and rollback
- Fluency in Python and SQL
- Ability to work with messy, fragmented customer data
- Ability to manage two or three customer engagements concurrently without a fixed sprint plan
- Exceptional communication skills for explaining technical work to executives and engineers
- Product mindset focused on creating reusable capabilities across customers
- B2B go-to-market data experience, including CRM, marketing automation, intent, ABM, or predictive scoring
- Experience explaining model outputs to nontechnical users
- Experience leading a small team or portfolio of client engagements
- Experience building or evaluating LLM-based tools and agents
- Experience with SingleStore, Hive, or Spark data platforms on AWS
6sense Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about 6sense and has not been reviewed or approved by 6sense.
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Fair & Transparent Compensation — Pay is considered strong overall, with widespread satisfaction in salary, benefits, and equity. Compensation is also positioned as comparatively competitive for multiple roles, including sales and engineering.
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Leave & Time Off Breadth — Time-off policies are described as flexible, including an unlimited-style vacation approach and expectations of being work-free while out. This breadth in paid time off is repeatedly positioned as a standout part of the overall package.
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Healthcare Strength — Health coverage is characterized as comprehensive, with dental and vision coverage called out as employer-paid in some descriptions. Wellness-related supports such as wellness days and stipends add to the perceived strength of the health-and-wellbeing offering.
6sense Insights
What We Do
The 6sense Account Engagement Platform helps revenue teams identify and close more opportunities by putting the power of AI, big data and machine learning behind every member of the B2B revenue team.
