ML Data Scientist — Travel Tech, End-to-End Analytics

Launch Potato; Buenos Aires; Hybrid; ARS 106,019,000 - 151,455,000; Full time

Benefits offered by this job

Hybrid Environment

Travel Benefits

Competitive USD Remuneration

Job summary

ID90 Travel is seeking a Data Scientist to bridge analytics and business goals. You will own data science initiatives end-to-end, analyze travel datasets, build models, and provide actionable insights that drive airline employee travel solutions.

The role is full-time, based in Córdoba with hybrid work, paid in USD, and requires 3+ years of DS experience, Python, SQL, and strong communication. Collaborate with product and engineering, deploy production models, and contribute to data-driven

Qualifications

• 3+ years of experience in Data Science, Statistics, ML, or related field.
• Bachelor's, Master's, or Ph.D. in quantitative field or equivalent practical experience.
• Proven experience applying statistical, analytical, and ML techniques to real-world problems.
• Experience owning DS projects from problem definition through production deployment.

Responsibilities

• Own Data Science Projects End-to-End from problem to deployment.
• Turn business questions into well-defined data problems and measurable goals.
• Collaborate with stakeholders to deliver data-driven solutions.
• Design, validate, and deploy models for business value.

Skills

Python

SQL

Statistics

Machine Learning

Data Analysis

Education

Bachelor's in Statistics/Math/CS

Master's in DS/CS (preferred)

Tools

Docker

PostgreSQL

Pandas

Job description

ID90 Travel is seeking a Data Scientist to bridge analytics and business goals. You will own data science initiatives end-to-end, analyze travel datasets, build models, and provide actionable insights that drive airline employee travel solutions.

The role is full-time, based in Córdoba with hybrid work, paid in USD, and requires 3+ years of DS experience, Python, SQL, and strong communication. Collaborate with product and engineering, deploy production models, and contribute to data-driven