Senior Data Scientist

Kard is transforming customer loyalty with our rewards-as-a-service API platform. We empower our partners, from neobanks to financial institutions and beyond, to offer tailored rewards that celebrate customers' daily transactions. Backed by $30M from industry-leading investors and seasoned experts, we are reshaping the future of customer engagement.

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.

Kard recognizes the unique value each of us brings to our collective success. As part of our remote-first team, you'll have the autonomy to influence our trajectory, actively contributing to the growth of our business and the evolution of our company culture. By embodying our core values of Initiative, Openness, and Humility, you will not only witness but directly foster an inclusive and dynamic work environment, from the executive level down.

• Flexible PTO, with a minimum requirement to take one day off a quarter, ten days a year, promoting mental well-being
• Observance of 11 Federal Holidays, plus an additional day each for Black Friday and Christmas Eve (US employees only)
• Health, Dental and Vision Insurance
• 401k with employer match (US employees only)
• Coworking space and WFH setup reimbursement
• Company Offsites two times per year for planning, team-building, and networking