Operations Data Analyst

myPOS

Sofia or Varna, Bulgaria

We are seeking a detail-oriented Operations Data Analyst to join our Operations team. In this role, you will be responsible for analysing data across Customer Support, Risk, KYC/KYB and Human Resources departments, providing actionable insights to improve operational performance and supporting data-driven decision-making. You will work closely with those departments to ensure that operational strategies are aligned with broader company objectives.

What you’ll do:

Operational Data Analytics: Analyse and interpret data related to Customer Support, Risk, KYC/KYB and HR processes to provide actionable insights that drive operational efficiency, forecast trends, and identify growth opportunities;
Performance Reporting: Develop and maintain performance reports, dashboards, and KPIs, ensuring accurate tracking of key operational metrics;
Workforce Planning & Optimization: Collaborate with HR leadership to develop accurate workforce forecasts by analysing historical data, market trends, and department performance;
Process Improvement: Identify opportunities to optimize workflows through data analysis, providing recommendations on resource allocation, process automation, and service delivery enhancements;
Data Integration & Management: Ensure data accuracy and consistency across various operational systems, collaborating with cross-functional teams to optimize data flows and integrations;
Customer Support Analytics: Monitor customer support data, identifying bottlenecks and inefficiencies. Provide actionable recommendations to improve response times, case resolution, and customer experience;
KYC/KYB Process Analysis: Support the Onboarding team by analysing data from KYC/KYB processes, highlighting trends, and identifying potential risks to improve compliance operations;
Automating decision-making engine: Analyse data rulesets for KYC & KYB data to drive improvements in verification engine;
Risk Management Analytics: Analyse data related to risk operations, such as transaction limits, fraud rates, chargebacks, card cashbacks, monitor performance of transaction monitoring rules to minimize operational risk while enabling revenue growth. Provide insights that help identify fraud patterns, mitigate losses, and enhance risk management strategies;
Cross-Department Collaboration: Partner with teams in HR, Customer Support, Risk and KYC/KYB to align data insights with broader company objectives, ensuring a cohesive approach to operational strategy;
Strategic Insights: Support operational leadership in strategic planning by delivering insights that inform decision-making, such as workforce planning, customer segmentation, and compliance analysis;
Training & Adoption: Assist in the adoption of new analytics tools and techniques within the operations teams, ensuring that stakeholders understand and utilize data-driven insights effectively.

What you bring:

Required:

Education: Bachelor’s degree in Business, Data Science, Economics, or a related field;
Experience: Proven experience (3-5 years) in data analytics, process-oriented or a similar role;
Technical Skills: Proficient in Microsoft Excel;
Operational Acumen: Strong understanding of key operational KPIs, process optimization, and performance forecasting methodologies;
Analytical Mindset: Ability to interpret complex data sets and translate them into clear, actionable insights that support operational performance and business growth;
Business Acumen: Solid understanding of operational strategies, market trends, and how data can be leveraged to optimise outcomes;
Customer centricity: Ability to analyse data to improve customer satisfaction and create seamless customer experience;
Collaboration & Communication: Strong stakeholder management skills with the ability to effectively communicate data insights to non-technical audiences, including HR, Customer Support, Risk and KYC/KYB leadership.

Preferred:

Experience with KYC/B and Risk decision making tools would be considered strong advantage;
Experience with HRIS and CRM platforms;
Knowledge of compliance and customer support operations;
Project management experience, particularly in managing data-related operational initiatives;
Familiarity with machine learning algorithms and their application in operations analytics.

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