Assistant Manager

Job Purpose

This role is placed under the ‘Data Insights’ team of EXL’s Emerging Business Unit (EBU) which is an amalgamation of Utilities, Travel, Transportation, Banking and F&A businesses. The ‘Data Insights’ team will play a critical role in identifying key data sources, creating strong data ingestion and management practices, generating data-driven insights and presentations. This is with the objective of optimizing operations, improving end-customer experience, generating client business insights, support continuous improvement, drive transformation leading to eventual growth of the business. 

We are seeking a skilled Data Analyst who has a strong foundation in data analytics, experience working with large datasets, and expertise in analysing operational performance and business metrics. A good understanding of analytics, insight and visualization tools and techniques will be preferred to generate key data storytelling and communication to stakeholders.

Skills & Experience 

              Essential skills and experience - minimum criteria 

• Education:
  • Bachelor’s degree (any) 
• Experience:
  • 3+ years of experience in data analysis, preferably within a BPM, or voice process environment.
  • Proven experience in analyzing operational metrics
• Technical Skills:
  • Proficiency in data analytics tools and platforms such as SQL, Excel.
  • Experience with scientific analytics tools like Python, R, or SAS for statistical analysis and model development.
  • Competent with data visualization tools such as Tableau or Power BI.
  • Knowledge of statistical techniques, including regression analysis, hypothesis testing, clustering, and machine learning.
  • Familiarity with natural language processing (NLP) techniques and tools for analyzing voice data.
• Soft Skills:
  • Strong analytical thinking and problem-solving skills.
  • Ability to communicate complex data insights clearly and effectively to non-technical stakeholders both verbally and through presentations.
  • Excellent organizational skills, attention to detail, and ability to manage multiple tasks simultaneously.

Desirable skills and experience 

• Education in Statistics, Computer Science, Operations Research, or a related field.
• Advanced degree or certification in Data Analytics, Business Intelligence, or related fields is a plus.
• Experience and knowhow in the travel industry and/ or a voice environment is a plus.

Responsibilities 

• Data Collection and Analysis:
  • Gather, clean, and analyze data from various sources, including performance metrics, customer satisfaction (CSAT) scores, and operational KPIs.
  • Develop efficient ways of managing and storing large data sets
  • Work with different stakeholders to ensure the data is accurate, accessible, and aligned with business goals.
  • Conduct exploratory data analysis (EDA) to uncover trends, patterns, and insights in voice process operations.
  • Evaluate call volumes, average handling times (AHT), first call resolution (FCR), and other non-voice metrics to identify operational gaps.
  • Familiarity with natural language processing (NLP) techniques and tools for analyzing voice data.
• Reporting and Dashboards:
  • Develop and maintain regular and ad-hoc reports and dashboards to monitor performance, agent productivity, and customer experience. 
  • Provide actionable insights through clear visualizations and presentations to clients, management and cross-functional teams using tools such as Tableau and/or Power BI.
• Root Cause Analysis:
  • Perform in-depth analysis to identify the root causes of process inefficiencies, customer dissatisfaction, and operational bottlenecks.
  • Use data to identify areas for improvement, such as call routing, agent performance, and resolution times.
• Scientific Analytics and Statistical Techniques:
  • Apply scientific analytics tools and techniques, such as regression analysis, hypothesis testing, and A/B testing.
  • Work with predictive models to forecast call volumes, staffing needs, AHTs and potential customer outcomes based on historical data.
• Optimization:
  • Collaborate with operations managers, SMEs, quality teams, WFM and other stakeholders to implement data-driven strategies for improving processes and enhancing customer service.
  • Use data to drive decisions related to process automation, resource allocation, and quality improvements.
• Stakeholder Collaboration:
  • Present and communicate complex data findings in a clear, concise and actionable manner to both technical and non-technical stakeholders.
  • Craft presentations with clear and powerful messages and cohesive story telling
• Continuous Improvement:
  • Monitor and track the relevance, impact and feedback of previous insights and continuously refine data models, metrics, and reporting strategies to support ongoing process optimization.
  • Stay updated on the latest trends in relevant industries, and scientific analytics techniques.