Internet Brands is looking to apply data science, machine learning, and statistical techniques to discover and operationalize user signals from their legal product and adjacent service ecosystem, identify niche audiences, and enable targeted marketing and growth initiatives.
Requirements
- SQL, Python/R, PySpark, warehousing, ETL orchestration and experience building production data products.
- Hands-on experience with segmentation, clustering, propensity/score modeling, uplift modeling, survival analysis, and causal inference.
- Familiarity with product analytics, CDP/DMP tooling, and marketing systems.
- Deep appreciation for data privacy, confidentiality, and ethical considerations when working with sensitive legal data.
Responsibilities
- Turn consumer signals into actionable insights to boost marketing performance, efficiency, and revenue through robust data collection, transformation, normalization, and cleaning.
- Lead development of feature pipelines and data products that surface intent, risk, and propensity signals relevant to legal consumers and their essential needs.
- Build rigorous audience discovery processes: cohort analysis, micro-segmentation, propensity modeling, lookalike creation, and transactional value estimation for niche legal segments.
- Partner with Marketing to translate signals into targeting strategies across paid acquisition, content personalization, and nurture campaigns; measure and iterate on channel-level performance.
- Establish instrumentation, tagging, and event taxonomy standards to ensure signal quality, provenance, and reusability across teams.
- Ensure all data collection and use adheres to confidentiality requirements, and privacy/regulatory constraints (e.g., GDPR, CCPA); coordinate with Legal and Compliance on guardrails.
- Design and run experiments and uplift analyses to validate causal impact of targeted campaigns and segmentation strategies (A/B testing, holdouts, synthetic controls).
Other
- Bachelors or advanced degree with a strong emphasis in Econometrics, Economics, or other quantitative disciplines.
- Demonstrated track record discovering/synthesizing user signals and turning them into commercial outcomes (lead generation, conversion lift, and/or revenue optimization).
- Excellent stakeholder management and communication skills; ability to translate technical outputs into clear marketing and product recommendations.
- Knowledge of legal consumer journeys.
- Collaborate effectively in cross-functional, multidisciplinary teams and champion knowledge sharing and peer mentorship.
