Data Analyst- Transaction Switching & Payment Processing at Interswitch

JOB PURPOSE

• To provide insights to the Product Management and Innovation team through the identification, collation and analysis of data from various sources to enable data backed decision making.
• To work on big data and analytics projects that gather and integrate large volumes of data, perform analysis, interpret results and patterns, and develop actionable insights and recommendations for 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 tests and initiatives.

Responsibilities

Data Collection, Analysis, Insights and Reporting

• Collate data using pre-set tools, methods and formats and perform deep dive analysis to understand drivers of products and platforms performance and customers’ behaviours, identify investment opportunities for growth, expand and sustain Interswitch’s user base and to shape ongoing and future enhancements.
• Consult regularly with cross-functional stakeholders to discuss data and analytic needs and advise functions on optimal use of available data, analysis, reports and models to support those needs.
• Contribute to the preparation of various data and analytics reports.
• Build and maintain the Interswitch’s data warehouse to support reporting, analysis, dimensional modelling and data development for internal and external stakeholders.

Promoting Customer Focus (Business Support and Advice)

• Help others get the most out of data management systems by providing support and advice.
• 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.
• Support interpretation of advanced and predictive analytics data, using specialised software tools and functionalities.
• Support data-driven analysis to identify opportunities for product / service improvement.
• Serve as an advocate for data-driven product design, evangelise insights on what is working and what is not to help drive incremental gains in pipeline and revenue.
• Act as mentor and coach to team members while fostering an environment of mutual respect and trust among senior- level team members.
• Work collaboratively with colleagues to build strong customer relationships and meet customer needs.

Improve Data and Analytics Platforms, Systems and Processes

• 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.
• Research and interpret data, trends, and benchmarks relevant to digital products / services design.
• Make recommendations to improve data and analytics systems and platforms, contributing to the continuous improvement and refinement of data and analytics strategy.
• Support the advancement of Interswitch’s analytics engineering framework, including scoping of new data models, rigorous documentation of data models and schemas, and standardisation of processes and workflows throughout thebroader data organisation.
• Analyse Interswitch’s funnels, identify areas of improvement, and brainstorm ways to leverage user experience, conversion and profitability.

BEHAVIORAL COMPETENCIES

Manages Complexity

• Makes sense of complex, high quantity, and sometimes contradictory information to effectively solve problems.

Plans and Aligns

• Plans and prioritises work to meet commitments aligned with organisational goals. For example, outlines clear plans that put actions in a logical sequence; conveys some time frames. Aligns own work with relevant workgroups. Takes some steps to reduce bottlenecks and speed up the work.

Tech Savvy

• Anticipates and adopts innovations in business-building digital and technology applications. For example, investigates technologies to learn some cutting-edge best practices. Uses digital / social media to benefit the team and add value to the work being done; understands how to avoid misuse of these tools.

Ensures Accountability

• Holds self and others accountable to meet commitments. For example, accepts responsibility for own work, both successes and failures. Handles fair share and does not make excuses for problems. Usually meets commitments to others.

Cultivates Innovation

• Creates new and better ways for the organisation to be successful. For example, approaches professional work in unique or innovative ways. Offers original ideas. Appreciates others' creative ideas and solutions and provides helpful input to enhance them.

Collaborates

• Builds partnerships and works collaboratively with others to meet shared objectives. For example, readily involves others to accomplish goals; stays in touch and shares information; discourages "us versus them" thinking; shows appreciation for others' ideas and input.

Optimises Work Processes

• Knows the most effective and efficient processes to get things done, with a focus on continuous improvement.

Communicates Effectively

• Develops and delivers multi-mode communications that convey a clear understanding of the unique needs of different audiences.

Customer Focus

• Builds strong customer relationships and delivers customer-centric solutions.

Balances Stakeholders

• Anticipates and balances the needs of multiple stakeholders. For example, draws upon insights from varied sources to gain a rich understanding of how to meet the needs of multiple internal and external stakeholders. Probes deeply in order to gain a rich, detailed grasp of the priorities of different stakeholders; takes initiative to respond to stakeholder problems.

TECHNICAL COMPETENCIES

Data Collection, Analysis and Control

• Works without supervision and provides technical guidance when required on analysing data trends for use in reports to help guide decision making.
• Works without supervision and provides technical guidance when required on acquiring, organising, protecting and processing data to fulfill business objectives.

Planning and Organising

• Works without supervision and provides technical guidance when required on planning, organising, prioritising and overseeing activities to efficiently meet business objectives.

Business Requirements Analysis

• Works without supervision and provides technical guidance when required on analysing the business requirements that IT solutions must meet. Determine acceptance and evaluation criteria; Prioritisation; Observation; Focus groups; Analysis Skills.

Review and Reporting

• Works without supervision and provides technical guidance when required on reviewing and creating relevant, lucid and effective reports.

Data Mining and Machine Learning

• Works with full competence to extract patterns from large amounts of data. Typically works without supervision and may provide technical guidance.

Customer Service Delivery

• Works without supervision while providing technical guidance as needed on meeting high customer service standards.

Customer-Focused Approach

• Works without supervision and provides technical guidance when required to orient the seller's organisation around delivering to the key needs of their customers. Collaborates with customers; Elevates partner insights; Keeps customer at center of sale; Uses common terminology.

Customer System Operation

• Works without supervision and provides technical guidance when required on understanding and effectively operating all customer management systems.

Data Conversion

• Works with full competence to use data conversion tools and techniques to encode data in various formats. Typically works without supervision and may provide technical guidance.

Data Compression

• Works with full competence to use data compression tools and techniques to reduce the size of data with minimal loss of information. Typically works without supervision and may provide technical guidance.

EDUCATION

• University First Degree in Computer Science, Engineering, Statistics, Mathematics or Finance-related field.

Experience

• At least 5 years' relevant experience in Data Analysis roles ideally within reputable financial institutions or the payments industry.

Deadlines: June 08, 2023