Lead Data Scientist, Customer & Growth Analytics

About The Role

Thomson Reuters Legal is seeking a Lead Data Scientist to help power data-driven growth and adoption of our AI-enabled legal solutions. In this role, you will design, build, and maintain predictive models—including propensity-to-upgrade models—that identify customers most likely to expand into AI products such as CoCounsel. You will work closely with Lifecycle Marketing, Marketing Operations, and Customer Success to ensure insights and models are not only accurate, but actionable—embedded directly into our Customer Data Platform (Treasure Data) and downstream activation workflows.

Responsibilities

• Design, build, and maintain predictive models that support customer expansion, including propensity-to-upgrade and engagement scoring models.
• Use behavioral, usage, firmographic, and lifecycle data to identify signals that indicate readiness for AI adoption and expansion.
• Partner with Lifecycle Marketing to translate model outputs into actionable segments and testable hypotheses across the customer lifecycle.
• Collaborate closely with Marketing Operations to operationalize models within the Customer Data Platform (Treasure Data) for activation and measurement.
• Develop features and datasets using product usage data, campaign engagement, learning activity, and customer attributes.
• Validate, monitor, and continuously improve model performance, ensuring accuracy, explainability, and alignment to business outcomes.
• Document modeling approaches, assumptions, and outputs to enable transparency, reuse, and cross-functional understanding.
• Work cross-functionally with Data Engineering, Product, Customer Success, and Commercial teams to ensure data quality and aligned outcomes.

Requirements

• 5+ years of experience in data science, analytics, or applied machine learning in a B2B SaaS or subscription-based environment.
• Experience building predictive or classification models that influence customer growth, retention, or expansion decisions.
• Strong proficiency in Python or similar data science tools, including feature engineering and model evaluation.
• Demonstrated experience working with large, complex datasets such as product usage, behavioral logs, or campaign data.
• Experience partnering with Marketing, Growth, or Customer Success teams to translate insights into action.
• Familiarity with deploying or activating models within analytics platforms or CDPs; experience with Treasure Data or similar platforms is a plus.
• Strong understanding of experimentation, model validation, and measuring impact using both statistical and business metrics.
• Ability to clearly communicate technical concepts and insights to non-technical stakeholders.
• Curiosity and ownership mindset, with a strong bias toward building models that are used and deliver measurable outcomes.

Qualifications

• Master's degree in Computer Science, Statistics, Mathematics, or related field.
• Proven track record of successful model deployment and implementation.
• Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-Learn.
• Knowledge of statistical analysis techniques and data visualization tools.
• Experience with customer segmentation and targeted marketing strategies.
• Excellent problem-solving and analytical skills.

Skills

• Data manipulation and cleaning using Python or R.
• Model training and validation using machine learning libraries.
• Feature selection and engineering techniques.
• Statistical analysis and hypothesis testing.
• Customer segmentation and targeting.
• Collaboration with cross-functional teams.
• Effective communication of technical concepts to non-technical stakeholders.

Benefits

This role offers a competitive benefits package including:

• Flexible vacation, sick, and safe time off.
• Paid holidays (including two company mental health days off).
• Parental leave and sabbatical leave.
• Market competitive health, dental, vision, disability, and life insurance programs.
• A competitive 401(k) plan with company match.
• Comprehensive wellness programs including access to Employee Assistance Program, Group Legal Identity Theft Protection benefit, and more.
• Optional hospital, accident, and sickness insurance.
• Access to Employee Stock Purchase Plan.

Pay

The base compensation range for this role is $137,100 USD - $254,700 USD.

Schedule

The role is available on a hybrid schedule with 2-3 days in the office per week.