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.