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ONEX LLC

Armenia

74519

views

148

job history

Industry:

Logistics/Courier

Number of Employees:

50-200

Type:

LLC/OJSC/CJSC

Date of Foundation:

2015

Customer Service Data Analyst

Full time

Yerevan

Employment term Permanent

Category Data Research/Analysis

Job description:

We are looking for a highly motivated and detail-oriented Customer Service Data Analyst to join our innovative team!

Job responsibilities
  • KPI Monitoring: Maintain key performance indicators (KPIs) to track and measure customer success and satisfaction. Generate regular reports to share insights with stakeholders.
  • Data Collection and Analysis: Collect and analyse customer data, including usage patterns and feedback to identify trends and insights that inform decision-making.
  • Customer Segmentation: Segment customers based on various criteria such as product usage, behaviour, and feedback to tailor engagement strategies and support initiatives.
  • Customer Feedback Analysis: Analyse customer feedback and survey responses to gain insights into satisfaction levels and areas for improvement. Translate feedback into actionable strategies.
  • Cross-functional Collaboration: Collaborate closely with Customer Success, Sales, Marketing, and Product Development teams to share insights and influence strategies for enhancing customer success.
  • Automation and Tools: Implement and maintain data automation processes and tools to streamline data collection and reporting.
  • Continuous Improvement: Stay updated on industry trends and best practices in customer success analytics to continuously improve our approach.
Required qualifications
  • Bachelor's degree in Data Science, Math, Statistics, Business Analytics, or a related field.
  • Proficiency in data analysis tools and languages (e.g., Excel, SQL, Python, R or SAS).
  • Experience with data visualization tools.
  • Strong analytical and problem-solving skills, with the ability to interpret complex data sets.
  • Knowledge of English and ability to communicate in it.
  • Detail-oriented and able to manage multiple data sources efficiently.
Additional information

Please note, that the working schedule is 9 a.m. -  6 p.m. from Monday to Friday and 10 a.m. - 2 p.m. on Saturday.