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 Job Offer: Unveiling the Role of a Data Professional in Digital Banking

As financial institutions accelerate digital transformation, the role of the data professional in digital banking has become central to strategy, operations, product development and risk management. Employers now seek individuals who do more than run analytics: they must design and operationalize data solutions that enable real‑time decisioning, regulatory compliance, customer experience improvement and new revenue streams. This article outlines the core responsibilities, required skills, value delivered, and considerations for organizations and candidates.

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Core responsibilities

- Data strategy and governance: Defining data architectures, cataloguing assets, and establishing governance frameworks that ensure data quality, lineage and compliance with banking regulation (e.g., privacy, AML/KYC).  

- Engineering and integration: Building and maintaining pipelines for ingesting, transforming and serving large volumes of structured and unstructured data; enabling real‑time and batch processing across legacy systems and cloud platforms.  

- Analytics and machine learning: Developing descriptive, predictive and prescriptive models supporting credit scoring, fraud detection, personalization and operational optimization; validating models for robustness and fairness.  

- Stakeholder collaboration: Translating business objectives into data use cases, partnering with product, risk, compliance and IT teams to operationalize insights and deliver business value.  

- Operationalization and adoption: Deploying models into production, monitoring performance, managing model drift, and ensuring adoption through change management and clear KPIs.

Skills and competencies

- Technical: Proficiency in data engineering (ETL, streaming), databases, big data technologies, cloud platforms, and ML toolchains. Familiarity with APIs and integration patterns in banking ecosystems is critical.  

- Analytical: Strong statistical reasoning, model development and validation skills, with the ability to explain complex outputs to non‑technical stakeholders.  

- Domain knowledge: Understanding of banking products, regulatory requirements, payments flows and risk frameworks to craft relevant and compliant solutions.  

- Governance and ethics: Practical experience implementing data governance, privacy controls, and responsible AI practices.  

- Communication and leadership: Ability to influence senior management, form cross‑functional teams, and translate technical capability into measurable business outcomes.

Value delivered

Data professionals unlock multiple sources of value for digital banks. They enable superior customer experiences through personalization and frictionless journeys; reduce loss via advanced fraud and credit risk models; increase operational efficiency by automating decisioning; and create new revenue streams through data‑driven products and partnerships. Moreover, robust governance reduces regulatory and reputational risk, an essential outcome in highly regulated banking environments.

Hiring considerations for employers

Employers should define whether they need specialists (e.g., ML engineers, data engineers, model validation experts) or hybrid professionals who can bridge business and technical domains. Effective job offers specify clear objectives (use cases to be delivered), measurable outcomes, technology stack, and governance expectations. Cross‑functional reporting lines and access to production systems accelerate impact. Investment in training and ethical guardrails will improve retention and compliance.

Considerations for candidates

Candidates should highlight concrete use cases they have delivered, measurable business impact, and experience navigating regulatory constraints. Demonstrable experience with real‑time systems, cloud deployments and model operationalization distinguishes top applicants. Soft skills stakeholder management, storytelling, collaboration are equally important.

Conclusion

The data professional in digital banking is a linchpin for transformation. As banks migrate services online and rely on data‑driven decisioning, these roles will remain strategic—requiring a blend of engineering rigor, analytical skill, domain understanding and governance discipline. Well‑crafted job offers that articulate business problems, technical environment and governance expectations attract the talent necessary to turn data into competitive advantage.