JETNET is seeking a highly skilled Data Scientist to help advance our aviation intelligence capabilities by improving how we analyze, connect, enrich, and operationalize our data. This role sits at the intersection of data science, data operations, product strategy, and domain expertise.

The ideal candidate will be more than a model builder. We are looking for someone who can evaluate large and complex datasets, identify where our data creates the most value for customers, and help build intelligent systems that improve data quality, surface meaningful relationships, and guide internal teams toward the highest-impact work.

This person will use predictive analytics, machine learning, relationship modeling, AI-assisted workflows, and customer usage analysis to help JETNET better understand which data matters most, how customers use it, where gaps exist, and how we can improve both internal efficiency and customer-facing value.

A critical part of this role is maintaining a human-in-the-loop approach. We do not want to replace the knowledge and judgment of our research and data teams. We want to give them better signals, better prioritization, better recommendations, and better tools so they can focus their expertise where it creates the most value.

What This Role Will Focus On

·   Predictive analytics to understand data value, customer behavior, product usage, viewership trends, and propensity to use specific data assets or features.

·   Analysis of data sources to determine whether we are utilizing them properly and where additional enrichment, cleanup, or productization would create the highest customer impact.

·   Relationship intelligence across aircraft, companies, contacts, owners, operators, transactions, and other aviation-related entities.

·   AI-assisted workflows that surface suggested records, relationships, gaps, and cleanup opportunities for internal team review.

Required Qualifications

·   Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Information Systems, or a related technical or quantitative field.

·   Strong hands-on experience with Python and SQL for data science, analytics, or data engineering work.

·   Demonstrated experience developing predictive models or analytical frameworks that influenced business decisions or operational workflows.

·   Experience working with large, complex, messy, or multi-source datasets.

·   Experience identifying patterns, relationships, trends, anomalies, gaps, or inconsistencies in data.

·   Strong understanding of data quality concepts, including completeness, accuracy, consistency, duplication, and timeliness.

·   Experience building or contributing to production-grade analytics, ML, or AI-assisted systems.

·   Proven ability to partner with business stakeholders, product teams, subject matter experts, and technical teams.