Senior Data Scientist

Kard is building commerce media infrastructure that connects financial institutions, financial-services platforms, and merchants through data and merchant-funded rewards. As our reach expands, we are building for a step-change in scale, and for opportunities ranging from more relevant rewards and marketer intelligence to new commerce and distribution models.

About the Role

As a Senior Data Scientist at Kard, you will build and deploy machine learning and experimentation systems that power our card-linked offers platform. Your work will directly improve how users discover and engage with offers, and how partners measure ROI. You’ll operate across personalization, ranking, and causal measurement - partnering closely with Product, Engineering, and Sales to turn behavioral transaction data into production-grade models and insights.

Responsibilities

• Build and ship ML models that drive offer personalization, ranking, and targeting using transaction, merchant, and user behavioral data.

• Develop features and training pipelines on top of large-scale event and transaction datasets (e.g., spend patterns, visit frequency, merchant affinity).

• Design and analyze A/B tests and incrementality experiments to measure campaign and model impact.

• Apply causal inference methods (e.g., matching, uplift modeling, diff-in-diff) to quantify partner ROI and user behavior changes.

• Partner with ML and Data Engineers to productionize models, including feature stores, batch/real-time scoring, and monitoring.

• Improve and iterate on ranking/recommendation systems to optimize engagement, conversion, and retention.

• Contribute to attribution and measurement systems that help brands understand incremental value from Kard campaigns.

• Translate complex modeling outputs into clear, actionable insights for internal teams and external partners.

• Own projects end-to-end: problem framing, data exploration, modeling, deployment, and post-launch evaluation.

• Help define best practices for experimentation, model evaluation, and data quality across the team.

Desired Skills

• 6+ years of experience in data science, with meaningful experience in applied machine learning in production.

• Strong experience with recommendation systems, ranking models, or personalization (e.g., propensity models, collaborative filtering, embeddings).

• Solid grounding in statistics and experimentation, including A/B testing and incrementality measurement.

• Experience with causal inference approaches for real-world observational data.