Senior Data Scientist

## 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. - Proficiency in Python (pandas, scikit-learn, PyTorch/XGBoost) and SQL; experience working with large-scale datasets. - Experience working with event-driven or transaction-level data (fintech, ads, marketplaces, or similar domains preferred). - Familiarity with modern data/ML stacks (e.g., Spark, Airflow, dbt, feature stores, cloud platforms like AWS/GCP). - Experience collaborating with engineers to deploy models into production systems (APIs, batch jobs, real-time scoring). - Ability to connect modeling work to business outcomes like conversion, lift, retention, and ROI. - Strong communication skills; able to explain tradeoffs and results to both technical and non-technical audiences. - Pragmatic, product-minded, and impact-driven. - U.S. core business hours availability and willingness to travel for company meetings. ## About the Company Kard is a card-linked offers platform.