Data Scientist (ML)

TL;DR

Data Scientist (ML): Designing and building algorithms for a workforce intelligence platform with an accent on automated data labeling and insight generation. Focus on developing classification models, optimizing SOP-driven experiences, and reducing manual user configuration.

Location: Remote (US)

Company

hirify.global is a workforce and workflow intelligence platform helping teams understand and improve how work gets done.

What you will do

• Design and build core intelligence and analytics algorithms to power the platform.
• Develop models for pre-labeling, classification, and structuring data to reduce manual user setup.
• Collaborate with ML engineers to productionize models and integrate them into scalable systems.
• Translate business problems into data-driven solutions in partnership with product and engineering.
• Build and iterate on models that generate insights, predictions, and recommendations.
• Analyze complex datasets to identify patterns, trends, and opportunities for product value.

Requirements

• Experience in applied data science, machine learning, or advanced analytics in a product-driven environment.
• Strong foundation in statistics, modeling, and experimental design.
• Hands-on proficiency with Python and common data science libraries.
• Strong SQL skills and ability to work with large, complex datasets.
• Ability to build and evaluate models that are ready for production.

Nice to have

• Experience with pre-labeling, weak supervision, or automated data labeling techniques.
• Familiarity with recommendation systems, classification, or predictive modeling.
• Experience working with ML engineers to productionize models.
• Understanding of workflow automation, process optimization, or operations analytics.
• Exposure to real-time data or event-driven systems.

Culture & Benefits

• High-impact role working directly with founders and engineers.
• Opportunity to build the intelligence layer of a growing platform.
• Flexible employment options, open to both part-time and full-time arrangements.
• Culture of high talent bar, ownership, and execution.