Senior Data Scientist Payments Digital Analytics

💼 Full-time🗓 2026-07-31

Core

Drive analytics, customer segmentation, and machine learning solutions for customer acquisition, activation, and digital payment usage campaigns in the payments/fintech domain.

Role type

Senior IC data scientist (payments/fintech)

Builds

Propensity/classification models, customer segmentation frameworks, campaign performance measurement frameworks, and analytics dashboards.

Domain

Fintech / Payments

Deliverable

production ML models | product features | dashboards & analysis

Required skills

Machine Learning lifecycle (EDA, feature engineering, training, deployment, monitoring), Python (Pandas, Scikit-learn, XGBoost/LightGBM), SQL, statistical modeling, customer segmentation, campaign analytics, A/B testing, causal inference, data pipelines (dbt, Airflow), data governance, PCI-DSS compliance

Preferred skills

Mobile money/digital payments (M-Pesa), remittance analytics, anonymization/privacy techniques, MLOps (MLflow, Vertex AI, SageMaker), emerging markets data environments

Technologies

Python, SQL, XGBoost, LightGBM, Airflow, dbt, Tableau, Power BI, Git, Azure, Jupyter, Jira

Responsibilities

Build and deploy propensity/classification models for customer acquisition and digital payment usage campaigns; Develop customer segmentation frameworks using transactional, behavioral, and demographic data; Design campaign performance measurement frameworks (A/B testing, attribution, digital lift analysis); Create analytics dashboards and reporting for campaign insights; Work with engineering teams to build and validate data pipelines; Ensure data quality, governance, PCI-DSS compliance, and privacy regulations; Support analytics initiatives for digital payments and remittance patterns; Document models, methodologies, and deliver knowledge transfer

Seniority

Senior, hands-on IC

Rewrite

## About the role We're looking for a Senior Data Scientist with 6+ years of experience to drive analytics, customer segmentation, and machine learning solutions in the payments/fintech domain. ## Key Responsibilities - Build and deploy propensity/classification models for customer acquisition, activation, card adoption, and digital payment usage campaigns. - Develop customer segmentation frameworks using transactional, behavioral, and demographic data. - Design campaign performance measurement frameworks (A/B testing, attribution, digital lift analysis). - Create analytics dashboards and reporting for campaign insights and digital adoption metrics. - Work with engineering teams to build and validate data pipelines for clean, reliable model inputs. - Ensure data quality, governance, PCI-DSS compliance, and privacy regulations in analytics workflows. - Support analytics initiatives for digital payments, remittance patterns, and customer behavior insights. - Document models, methodologies, and deliver knowledge transfer to internal teams. ## Required Skills - 6+ years in Data Science, with 4+ years in Payments, Fintech, Financial Services, or Telecom. - Strong experience in Machine Learning lifecycle (EDA, feature engineering, training, deployment, monitoring). - Expertise in Python (Pandas, Scikit-learn, XGBoost/LightGBM), SQL, and statistical modeling. - Experience with customer segmentation, campaign analytics, A/B testing, and causal inference. - Hands-on with data pipelines (dbt, Airflow, SQL) and dashboards (Power BI, Tableau, Looker). - Strong understanding of data governance, PCI-DSS, privacy, and data quality frameworks. ## Nice to Have - Experience in mobile money/digital payments (M-Pesa or similar). - Knowledge of remittance analytics, anonymization/privacy techniques, and MLOps (MLflow, Vertex AI, SageMaker). - Experience working in emerging markets data environments. ## Tech Stack Python | SQL | XGBoost | LightGBM | Airflow | dbt | Tableau | Power BI | Git | Azure | Jupyter | Jira

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