Overview
Lead Data Scientist (Marketing) to build and optimize marketing analytics and campaign modeling for direct mail and paid media.
What you'll do
- Design and build response models to predict customer engagement likelihood.
- Develop approval models to estimate lead approval probability for financial products.
- Analyze match backs to support direct mail and paid marketing decisions.
- Partner with marketing teams to design experiments, define KPIs, and measure effectiveness.
- Perform deep-dive analyses of direct mail and digital media campaign performance.
- Use model outputs and historical performance to drive targeting and segmentation.
- Ensure models are production-ready, monitor performance, and integrate results into execution pipelines.
What you'll need
- 8+ years of experience in data science focused on marketing, growth, or customer acquisition.
- Proven track record developing and deploying predictive models for marketing use cases.
- Strong proficiency in Python and ML libraries including Scikit-learn, XGBoost, PyTorch, or TensorFlow.
- Advanced SQL skills and experience with large-scale relational databases.
- Deep understanding of statistical testing, experiment design, and campaign performance analysis.
- Exceptional communication skills to present findings to non-technical stakeholders.
- Master’s or Ph.D. in Statistics, Computer Science, Engineering, or a related quantitative field.
Nice to have
- Experience with direct mail targeting, paid media optimization, or acquisition funnel analytics.
- Background in fintech, credit products, or regulated industries.
- Familiarity with MLOps, particularly in the AWS ecosystem, and workflow tools like Apache Airflow.
- Experience with uplift modeling, lookalike modeling, or media mix optimization.
Details
- Hybrid work model with in-office days determined by location and discipline.
Read the full description and apply on the company’s own careers page.
