Data Scientist (Generative AI)

TL;DR

Data Scientist (Generative AI): Partnering with clients to prepare, clean, and transform data for seamless integration with the aiCast platform, and building pipelines, dashboards, and forecasts with an accent on data engineering, applied analytics, and client enablement. Focus on end-to-end implementation from ingestion through delivery, solving complex data quality issues, and translating technical work into business impact.

Company

hirify.global unlocks the power of generative AI for tabular data through its proprietary platform built from years of MIT research.

What you will do

• Collaborate with clients to understand data sources, structures, and business requirements.
• Design and implement data transformation pipelines for aiCast ingestion.
• Build reporting and dashboarding solutions to help clients interpret and act on their data.
• Develop forecasting and analytics workflows to extend client use cases beyond data prep.
• Support end-to-end solution delivery—covering extraction, transformation, validation, and deployment.
• Troubleshoot data quality issues and provide recommendations for improved structures or processes.

Requirements

• At least 1-3 years of experience in a data role, preferably with enterprise clients.
• Associate’s or Bachelor’s degree in a relevant field (e.g., Computer Science, Statistics, or Applied Mathematics).
• Proficiency in Python, including libraries like NumPy and Pandas for data transformation.
• Working knowledge of SQL for querying and joining datasets (intermediate level).
• Experience building ETL/ELT pipelines or similar data processing workflows.
• Familiarity with data visualization, reporting, or dashboarding tools.
• Ability to work with incomplete or messy data and structure it for usability in production systems.
• Excellent communication skills for translating technical work into business impact.

Nice to have

• Knowledge of data transformation, database management, data integration, or data visualization.
• Experience with forecasting techniques or applied time-series analytics.
• Background in client-facing or consulting roles where you owned implementation delivery.
• Understanding of software engineering best practices (version control, testing, deployment).

Culture & Benefits

• Committed to equal employment opportunity and non-discrimination for all employees and qualified applicants.
• Focus on client outcomes and practical implementation.
• Opportunity to partner with internal engineering and success teams.