Senior Digital Data Scientist

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Reporting Line

HEAD OF DIGITAL BANKING

Location

Tanzania Head Office

Department

Department of Retail Banking

Number of openings

1

Job Purpose

The Senior Data Scientist is the principal technical architect and hands-on lead for the data science team. This role is responsible for designing, building and deploying highly scalable machine learning models that optimize digital banking products, predict customer behavior and manage risk.

The Senior Data Scientist bridges the gap between pure research and production engineering, ensuring the team's code is robust, automated and seamlessly integrated into live banking workflows.

Principle Responsibilities

• Design, train and validate complex predictive and prescriptive models (e.g., real-time credit scoring algorithms, predictive churn models and recommendation engines).
• Build scalable, repeatable feature engineering pipelines that process large volumes of digital banking log data, utilizing tools like PySpark and SQL.
• Package and containerize models (using Docker) and work with system architects to deploy them as low-latency microservices/APIs into production.
• Establish and enforce best practices for version control (Git), code modularity, documentation and automated testing across the data science pipeline.
• Peer-review and audit the mathematical frameworks and assumptions made in models built by junior data scientists to prevent overfitting, bias or data leakage.
• Actively mentor Junior Data Scientists, guiding them through complex algorithmic challenges, feature selection techniques and hyperparameter tuning.
• Stay at the forefront of AI/ML trends, assessing how new techniques (e.g., Large Language Models, advanced graph analytics for fraud detection) can be applied to digital banking.

Qualifications Required

• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
• Minimum of 4 years of professional experience as a Data Scientist, with a documented history of shipping machine learning models directly into production environments.
• Expert-level Python skills, with fluency in the data science stack (Scikit-Learn, Pandas, NumPy).
• Practical experience processing high-velocity transaction data using distributed computing frameworks, specifically PySpark/Spark.
• Strong proficiency with containerization (Docker) and setting up persistent metadata environments (e.g., interacting with a Hive Metastore backed by relational or object storage).
• Advanced SQL skills optimized for writing complex queries over large data stores (e.g., PostgreSQL oracle).
• The ability to look at a complex banking problem and architect an algorithmic solution.
• Ability to manage high-performing technical minds, fostering a collaborative, non-siloed engineering culture.
• Flexible and adoptive to market dynamics and experimentation.
• Customer-centric mindset.
• Self-driven and problem-solving skills.

CRDB Commitment

CRDB Bank is dedicated to upholding Sustainability and ESG practices and encourage applicants who share this commitment. The Bank also promotes an inclusive workplace, hence applications from women and individual with disabilities are encouraged.

It is important to note that CRDB Bank does not charge any fees for the application or recruitment process, and any requests for payment should be disregarded as they do not represent the bank’s practices.

Only Shortlisted Candidates will be Contacted.

Deadline

2026-06-30

Employment Terms

PERMANENT