Senior Data Scientist

Firma
Kard Financial
Lokacija
Remote
Nivo
Senior
Objavljeno
09.10.2026

Opis posla

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...

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