Senior Data Scientist

🕒 Abril 21

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Kard

SiteLinkedInTodas as Vagas

51 - 200 funcionários

🔌 API

💳 Fintech

☁️ SaaS

API • Fintech • SaaS

A Kard é uma empresa que oferece a primeira API de recompensas como serviço voltada para aprimorar a fidelidade do cliente para portadores de cartões e compradores. Ao fornecer ferramentas para profissionais de marketing e bancos lançarem programas de fidelidade personalizáveis rapidamente, a Kard os capacita a engajar portadores de cartões inativos e a incentivar compras repetidas. A plataforma da empresa é projetada com foco em segurança e conformidade, garantindo confiança em seus produtos. As soluções da Kard ajudam profissionais de marketing a alcançar novos públicos, emissores de cartões a criar programas de fidelidade com marca, e consumidores a ganharem recompensas de forma fácil em inúmeros locais nos EUA.

Descrição

• 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.

🎯 Requisitos

• 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.

🏖️ Benefícios

• 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