Data Scientist

To work on big data and data science projects that gather and integrate large volumes of data, perform analysis, interpret results and patterns and develop actionable insights and recommendations to inform decision making and enhance Interswitch’s products and platforms. To act as a strategic thought partner for cross-functional teams to both generate and evaluate the viability and impact of new data models and initiatives.

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.
• Identify and implement improvements to Interswitch’s data pipeline, such as better documentation, anomaly detection, alerting, and instrumentation.

Performance Improvement through Business Intelligence

• Support 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 enhance user experience, conversion, and profitability.

Data Collection and Analysis

• Collate and analyse data using pre-set tools, methods, and formats.
• Work cross-functionally to convert business needs into data science solutions and innovative products aligned with Interswitch’s strategy.
• Perform deep-dive data science and analysis to understand product and platform performance, customer behaviours, and identify growth opportunities.

Benchmarking and Identifying Opportunities

• Conduct industry benchmarking to identify improvement opportunities, data science, AI, and ML trends.
• Implement best practices to optimise revenue growth and brand preference.

Internal Communications

• Help teams maximise internal communication systems by offering support and advice.
• Serve as an advocate for data-driven product design, sharing insights on what is working and what is not.
• Act as a mentor and coach to team members while fostering an environment of mutual respect and trust.

Information and Business Advice

• Resolve complex queries from internal or external stakeholders by providing information on processes, policies, and analysis.
• Assist in building and prototyping analysis pipelines, including analytics algorithms, predictive models, acquisition and lifecycle analysis, customer segmentation, marketing attribution, and forecasting.
• Interface with business functions to share actionable insights from multiple data sources, guiding decision-making to improve products and platforms.

SKILLS

• Data Collection, Analysis and Control: Analyse trends, acquire, organise, and process data to fulfil business objectives.
• Business Requirements Analysis: Translate business requirements into actionable data science solutions.
• Policy, Procedures and Compliance Management: Develop, monitor, and ensure alignment with organisational policies.
• Application Development: Develop software using programming languages as needed.
• Verbal and Written Communication: Express ideas and plans clearly, guiding others when required.
• Architecture: Design architectures meeting system and service requirements.
• Presentation Skills: Communicate information clearly, concisely, and compellingly.
• Planning and Organising: Prioritise and oversee activities efficiently.
• Review and Reporting: Create accurate and actionable reports.
• Data Mining and Machine Learning: Extract patterns from large datasets, provide technical guidance.
• Customer Service Delivery: Meet high customer service standards and guide others.
• Project Management: Manage projects within cost, time, and quality parameters.
• Workflow Management: Plan, organise, and execute work efficiently, using tools like Kanban boards.
• Business Data Modelling: Analyse, model, and report data flow for strategic decision-making.
• Metadata Management: Create and manage metadata systems for information accessibility.
• Database User Interfaces and Queries: Create and run queries across various database interfaces.

EDUCATION

• University First Degree in Computer Science, Information Technology, Statistics, Mathematics, Finance, or related fields.

EXPERIENCE

• Minimum of 5 years in analytical roles, ideally within financial or fintech institutions.
• At least 3 years of experience in data science to enable independent handling of complex situations and guidance to others.

Due to the high volume of applications, only shortlisted candidates will be contacted.

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