Interswitch Limited is an integrated payment and transaction processing company that provides technology integration, advisory services, transaction processing and payment infrastructure to government, banks and corporate organizations. Interswitch, through its “Super Switchâ€Â provides online, real-time transaction switching that enable businesses and individuals have access to their funds across the 24 banks in Nigeria and across a variety of payment channels such as Automated Teller Machines (ATMS), Point of Sale (PoS) terminals, Mobile Phones, Kiosks, Web and Bank Branches.
Job Summary
- We are seeking a Data Scientist to work on big data and data science projects, gathering and integrating large volumes of data to perform analysis, interpret results, and develop actionable insights. This role involves providing strategic recommendations to enhance Interswitch's products and platforms while serving as a thought partner for cross-functional teams in evaluating the viability and impact of new data models and initiatives.
Key Responsibilities:
Data Architecture
- Consult and educate stakeholders on methods for streamlining and standardising data recording to ensure quality and accuracy.
- Build and maintain Interswitch’s data warehouse to support reporting, analysis, dimensional modelling and data development for internal and external stakeholders.
- Empower key stakeholders to access reliable, clean, business data by emphasising quality and best practices, identifying and implementing improvements to Interswitch’s data pipeline such as better documentation, anomaly detection, alerting and instrumentation.
Performance Improvement through Business Intelligence
- Support the creation of machine learning algorithms by applying standard statistical analysis or data preparation methods.
- Analyse Interswitch’s payment processing funnels, identify areas of improvement and brainstorm ways to leverage user experience, conversion and profitability.
Data Collection and Analysis
- Collate and analyse data using pre-set tools, methods and formats.
- Work cross-functionally to understand and convert business needs into data science solutions and new innovative products that will deliver on the payment processing agenda in line with Interswitch's business requirements and strategy.
- Perform deep dive data science and data analysis to understand drivers of products and platforms performance and customers’ behaviours, to identify investment opportunities for growth, to expand and sustain Interswitch’s user base and to shape ongoing and future enhancements.
Benchmarking and Identifying Opportunities
- Conduct industry benchmarking to identify improvement opportunities, data science, artificial intelligence and machine learning-related trends and best practices and implement them to optimise revenue growth and brand preference.
Internal Communications
- Help others get the most out of internal communications systems by offering support and advice.
- Serve as an advocate for data-driven product design, and evangelise insights on what is working and what is not to help drive incremental gains in pipeline and revenue.
- Act as a mentor and coach to team members while fostering an environment of mutual respect and trust among senior-level team members.
Information and Business Advice
- Resolve complex queries from internal or external customers or suppliers by providing information on policies and procedures, and referring the most complex issues to others.
- Assist in building and prototype analysis pipelines iteratively, including analytics algorithms, business enablers and models related to predictive analytics, acquisition, lifecycle stage, purchase propensity, customer segmentation, marketing attribution models and forecast, experimentation metrics, and data acquisition processes.
- Harness data that are applied to products that need to respond with payment processing analytics.
- Interface with business functions sharing actionable insights based upon multiple data sources to inform and assist decision-makers on the most expedient ways to improve and optimise products and platforms performance in cost, quality, delivery and user experience.
Requirements
Academic Qualification(s):
- University First Degree in Computer Science, Information Technology, Statistics, Mathematics, Finance or related fields
Experience:
- At least 7 years of relevant experience in Analytical roles ideally within financial or FinTech institutions.
Method of Application
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