Workforce Data Analyst

Holafly; Medellín; Hybrid; COP 24,000,000 - 42,000,000; Full time

Job summary

Holafly is seeking a Junior Workforce Data Analyst in Medellín, Colombia, with a strong analytical mindset to turn data into actionable insights. You will support the Conversational Commerce team by monitoring staffing, demand, and performance across markets, languages, and channels.

The role emphasizes data accuracy, scalable reporting, and responsible AI usage, working with Sales Growth, Training, and QA to optimize service levels and revenue opportunities.

Qualifications

• Bachelor's degree in Engineering, Data Analytics, BI, or related fields; a master's in Data Analytics is a plus.
• 1–3 years of proven experience as a Data Analyst or Sales/Rev Ops Analyst.
• Analytical mindset that connects operational data with business outcomes.
• Comfortable with KPIs, targets, trends, forecasts, anomalies, and performance analysis.
• Ability to explain complex data in a clear, business-oriented way.

Responsibilities

• Monitor and analyze operational, workforce, and commercial metrics across regions, markets, languages, channels, and teams.
• Build, maintain, and improve recurring reports, dashboards, trackers, and performance views for daily, weekly, and monthly decision-making.
• Support workforce planning: staffing needs, coverage gaps, peak hours, seasonality patterns, workload distribution, and capacity risks.
• Help forecast demand using historical data, business trends, seasonality, campaigns, and traffic behavior.
• Provide insights to improve scheduling, shift allocation, capacity planning, and regional coverage.
• Detect operational and commercial risks such as understaffing, overstaffing, low availability, rising response times, declining conversion, revenue leakage, or queue saturation.
• Partner with managers to turn data into action plans that improve productivity, customer experience, and sales performance.
• Ensure data accuracy, consistency, and reliability across reports, dashboards, trackers, and internal databases.
• Support deep dives into root causes behind changes in performance.
• Create clear executive summaries and business recommendations for leadership.
• Collaborate with Data, BI, Operations, and Sales teams to improve data sources, automate reporting, and reduce manual work.
• Use AI tools responsibly to accelerate analysis and automation.
• Promote data governance: accuracy, documentation, access control, responsible AI usage, and secure handling of sensitive business information.

Skills

Analytical mindset

Data-driven decisions

AI-first mindset

English communication

KPI analysis

Data validation

Attention to detail

Problem solving

Cross-functional collaboration

Education

Bachelor's degree in Engineering/Data Analytics/BI

Master's in Data Analytics (plus)

Tools

Google Sheets

Excel

Looker Studio

Power BI

SQL

BigQuery

Intercom

n8n

Supabase

Apps Script

Job description

Company Overview

Holafly is a fast-growing company changing the way travelers stay connected abroad. Since 2018, we have helped millions of travelers access mobile internet in more than 200 destinations worldwide.

The Role

Location: Medellín, Colombia (hybrid). Level: Junior. English: B2 minimum.

We are looking for a highly analytical, business-oriented, and AI-driven Workforce Data Analyst to support the growth, efficiency, and scalability of our Conversational Commerce team. Your mission is to turn workforce, operational, and commercial data into clear insights that improve service levels, optimize staffing, and maximize revenue opportunities.

You will work with Sales Managers, Sales Coordinators, the Sales Growth team, Training, and QA to monitor demand, identify risks, improve scheduling efficiency, and ensure the right coverage across markets, languages, channels, and time zones.

This role is not only about reporting. It is about connecting data with business decisions: how chat volume, staffing, response times, conversion, customer experience, and sales performance shape the results of the operation.

We also want someone who uses AI tools responsibly to analyze faster, automate workflows, and build scalable solutions from scratch when needed.

Key Responsibilities

• Monitor and analyze operational, workforce, and commercial metrics across regions, markets, languages, channels, and teams.
• Build, maintain, and improve recurring reports, dashboards, trackers, and performance views for daily, weekly, and monthly decision-making.
• Support workforce planning: staffing needs, coverage gaps, peak hours, seasonality patterns, workload distribution, and capacity risks.
• Help forecast demand using historical data, business trends, seasonality, commercial campaigns, and expected traffic behavior.
• Provide insights to improve scheduling, shift allocation, capacity planning, and regional coverage across AMER, EMEA, APAC, and other segments.
• Detect operational and commercial risks such as understaffing, overstaffing, low availability, rising response times, declining conversion, revenue leakage, or queue saturation.
• Partner with managers and coordinators to turn data into action plans that improve productivity, customer experience, and sales performance.
• Ensure data accuracy, consistency, and reliability across reports, dashboards, trackers, and internal databases.
• Support deep dives into the root causes behind changes in performance.
• Create clear executive summaries and business recommendations for leadership.
• Collaborate with Data, BI, Operations, and Sales teams to improve data sources, automate reporting, and reduce manual work.
• Use AI tools responsibly to accelerate analysis, structure information, generate documentation, build prototypes, automate repetitive tasks, and improve decision-making.
• Promote data governance: accuracy, documentation, access control, responsible AI usage, and secure handling of sensitive business information.

What We Are Looking For

• Professional with a degree in Engineering, Data Analytics, Business Intelligence, or related fields; a master's in Data Analytics is a plus.
• 1 to 3 years of proven experience as a Data Analyst, Sales/Rev Ops Analyst .
• Analytical mindset that connects operational data with business outcomes.
• Comfortable with KPIs, targets, trends, forecasts, anomalies, and performance analysis.
• Ability to explain complex data in a clear, simple, business-oriented way.
• Strong attention to detail and commitment to data accuracy.
• Proactive, structured, solution-oriented; comfortable in a fast-paced, international, performance-driven environment.
• AI-first mindset, with a strong sense of data responsibility (confidentiality, governance, validation, secure use of business information).
• English level B2 or higher.

Technical Skills

• Strong proficiency in Google Sheets or Excel.
• Dashboards and reports in Looker Studio, Power BI, or similar tools (intermediate to advanced)
• SQL knowledge (basic to intermediate) is highly desirable; BigQuery or similar data warehouse tools is a plus.
• Experience with data exports from CRM, chat platforms, workforce tools, or internal databases.
• Knowledge of data validation, cleaning, reconciliation, and reporting logic.
• Familiarity building with AI (not negotiable): analysis, documentation, workflow design, dashboard planning, query support, and automation.
• Understanding of responsible AI usage: data privacy, prompt hygiene, access control, and avoiding exposure of sensitive information in unsecured environments.

Nice to Have

• Previous experience in Workforce Management, Sales Operations, Business Intelligence, Customer Experience, or Contact Center Analytics.
• Experience analyzing chat, CRM, e-commerce, sales, or customer support operations.
• Understanding of global operations across time zones, languages, and regions.
• Experience supporting headcount planning, shift planning, service level analysis, or productivity models.
• Familiarity with Intercom, BigQuery, Looker Studio, Google Sheets, Apps Script, Supabase, n8n, or similar tools.
• Experience building tools, automations, dashboards, or prototypes from scratch using AI-assisted development.
• Basic understanding of data governance, documentation standards, metric definitions, and reporting ownership.