Sr. Data Scientist, Forward-Deployed

6sense • San Francisco, CA

7d

About The Position

6sense is hiring a Senior Data Scientist to serve as the lead modeler on its Forward Deployed Engineering (FDE) Predictive track. The role works hands-on with strategic customers’ production data to tailor, retrain, and validate models that help sales and marketing teams prioritize accounts and buyers. The position typically drives two or three customer engagements at a time and presents results in terms of business value. Successful work is captured as reusable capabilities for 6sense customers.

The role involves understanding customers’ go-to-market processes and data, including CRM, marketing automation, firmographic, and intent signals. The Senior Data Scientist retrains and tunes account and contact models, validates their impact through backtesting, calibrates score thresholds, and produces customer-ready deliverables. The person partners with an MLOps engineer to put solutions into production and shares recurring customer needs and reusable patterns with Product.

The position is on the Forward Deployed Engineering team, Predictive track, within Data Science & AI Engineering. It reports to the Director of Data Science, is classified as senior level, and is located in the United States. The posted base salary range is $168,349.50–$230,912.60. Additional compensation may include a bonus program or commission plan and, if approved, stock options.

Requirements

• 6–8 years of experience building and deploying machine learning models in production, ideally ranking, propensity, classification, or scoring models using tabular or behavioral data.
• Strong foundation in machine learning and applied statistics, including tree-based models such as XGBoost and Random Forest, model evaluation, and calibration.
• Fluency in Python and SQL.
• Experience working with large, messy, real-world datasets, including matching customer CRM records to account data.
• Experience working with or for customers on their data, such as consulting, client-site work, or a forward-deployed, solutions, or customer-facing data role.
• Ability to switch among several ad hoc projects in a week rather than focus on one long roadmap item.
• Ability to explain technical work clearly to non-technical audiences.
• A product mindset, seeking solutions that can work for future customers as well as the current customer.

Nice To Haves

• Experience with B2B go-to-market data, including CRM, marketing automation, intent, ABM, or predictive scoring.
• Experience with lead or contact scoring models.
• Experience with model explainability methods such as feature importance or SHAP.
• Experience with Spark, SingleStore, or Hive on AWS.
• Experience with LLM-based tools, agents, or evaluation methods.

Responsibilities

• Understand each customer’s go-to-market processes and data, including CRM, marketing automation, firmographic data, and intent signals.
• Retrain and tune account and contact models, including ideal customer profile and industry definitions, keyword strategy, CRM activity inputs, feature selection, and the balance of first- and third-party signals.
• Validate model impact through backtests against the live model and, where possible, the customer’s own scoring, using opportunity conversion by score bucket.
• Calibrate score thresholds and scaling to provide customers with a steady, explainable flow of qualified accounts.
• Create customer-ready review decks, explainability views, score files, and documentation that customers can verify.
• Partner with the team’s MLOps engineer to bring solutions into production and support their continued delivery after handoff.
• Capture lessons as reusable patterns and share recurring customer needs with Product, supported by field evidence.
• Present model results in terms of business value.

Benefits

• Health insurance and health coverage
• Life insurance
• Disability insurance
• 401(k) employer matching
• Paid holidays
• Self-care days and quarterly self-care days off
• Paid time off
• Paid parental leave
• Stock options
• Equipment and support for working and connecting with teams at home or in an office
• Learning and development initiatives, including access to LinkedIn Learning
• Quarterly wellness education sessions
• Wellness days and ERG-hosted events

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed