Sr.Officer - Commercial Data Intelligence

We are seeking a Sr. Data Officer to join Almosafer’s Data Intelligence team within the Commercial function. Your first priority will be to independently own analytics for the Workforce Management (WFM) and Quality Assurance (QA) teams, using contact center and quality data to report on agent productivity, staffing accuracy and service quality. You will also support the Fulfillment and Quotation Management teams with reporting on operational performance, Customer Impact Ratio and Service Level Agreements (SLAs), following Data Intelligence standards and governance.

The ideal candidate will have 3+ years of analytical experience, preferably in a contact center, e-commerce or travel business. They should have worked on call center, WFM or QA analytics and be comfortable with BI tools. Working knowledge of Gen AI tools, along with experience building simple Gen AI solutions, is required. Exposure to forecasting or rule-based models is a strong advantage.

Responsibilities:

• Workforce Management & Quality Assurance Analytics (Primary Focus):

Own WFM and QA analytics independently, from sourcing the data to building dashboards and running regular performance reviews.

Use data from platforms such as Infobip and Genesys to track agent productivity, handling time, occupancy, schedule adherence and service levels across calls and chats.

Measure demand forecast accuracy and workforce allocation (forecast vs. actual volumes and staffing), and flag gaps to the WFM team.

Analyze QA evaluation data to find quality trends, repeated errors, compliance gaps and coaching needs at agent and team level.

Redesign the current WFM and QA reports so they show near real-time performance, quality trends and compliance results.

Build forecasting and rule-based models to predict staffing needs, flag quality risks early and support workforce planning.

• Gen AI Usage & Development:

Use Gen AI tools (e.g., Claude, ChatGPT, Copilot) in daily work to speed up SQL, Python and dashboard development, documentation and analysis.

Build Gen AI solutions for WFM and QA, such as reviewing and summarizing call and chat transcripts, supporting QA scoring and drafting regular performance reports.

Follow Almosafer’s data privacy and governance policies whenever customer or agent data is used with Gen AI tools.

• Fulfillment & Quotation Management Analytics (Supporting):

Support Fulfillment (Air & Non-Air) reporting on SLA adherence, Customer Impact Ratio and operational bottlenecks.

Support Quotation Management (QM) reporting on quotation lifecycle, supplier responsiveness and case resolution KPIs.

• Advanced Analytics & Data Solutions:

Automate recurring reports and data pipelines using SQL, Python and cloud data platforms to reduce manual work.

Work with the Data Engineering and Governance teams to keep source data accurate and in line with enterprise data quality standards.

• Collaboration & Data Governance:

Act as the link between Operations (WFM, QA, Fulfillment) and Data Intelligence so that all teams use the same KPI definitions and methods.

Help operations teams understand and use data correctly and share good analysis practices across teams.

• Bachelor’s degree in STEM, Business Analytics or a related field.
• 3+ years of experience as a Data Analyst, preferably in a contact center, e-commerce, online travel agency or other digital business.

• Proficiency in SQL, Python or R, and advanced Excel.
• Experience in Workforce Management, Call Center or Quality Assurance analytics (e.g., AHT, service level, occupancy, adherence, shrinkage, QA scores).

• Regular use of Gen AI tools at work, and experience building Gen AI solutions (e.g., prompt design, context building, and creating or refining AI agents and automations).
• Experience building dashboards in Tableau, Power BI, Looker or similar BI tools and presenting findings clearly to stakeholders.

• Able to work independently, take full ownership of a domain and manage priorities with little supervision.
• Good stakeholder management and communication skills; English fluency.

• Exposure to forecasting or scoring models (e.g., volume forecasting, quality risk scoring) is a strong plus.
• Familiarity with cloud data platforms (e.g., AWS Athena, AWS Redshift, Google BigQuery, Snowflake).

Experience with Salesforce, Genesys, Infobip or similar contact center and fulfillment platforms is a plus.