Data Scientist (AI)

TL;DR

Data Scientist (AI/ML): Modeling accurate digital twin electric networks from imperfect data using AI, deep learning, and classical ML algorithms with an accent on geospatial data analysis and predictive modeling. Focus on designing scalable data pipelines for LiDAR and imagery, solving complex grid expansion challenges, and improving model reliability to prevent real-world disasters.

Location: Hybrid (Must be based in New York City, Dallas, Denver, or Houston)

Salary: $160k – $190k + Equity

Company

hirify.global creates physics-enabled digital twins of electricity grids using advanced machine learning to help utilities optimize investments and build a more resilient global energy future.

What you will do

• Develop digital twin electric networks using AI, deep learning, and classical ML algorithms.
• Generate meaningful analytics and metrics, such as wildfire risk, to guide infrastructure buildout.
• Inform hirify.global's strategy by providing deep insights derived from grid data.
• Conduct A/B tests and experiments to optimize the accuracy of grid modeling.
• QA predictive models by identifying data issues like distribution drift and overfitting.
• Build scalable data pipelines for multi-modal sources including LiDAR, aerial photography, and GIS.

Requirements

• 3-6 years of experience as a Data Scientist or ML Scientist at technical, data-driven companies.
• Demonstrated expertise in AI, Machine Learning, and data modeling.
• Proficiency in ETL technologies such as Parquet, Databricks, Snowflake, PostgreSQL, Spark, and DynamoDB.
• Experience working within an AWS cloud environment.
• Ability to translate models into deployable software and conduct experiments.
• Must be based in New York City, Dallas, Denver, or Houston for hybrid work.

Nice to have

• Experience working with geospatial data.
• Prior experience in the energy industry or with power grids.

Culture & Benefits

• Opportunity to work with a sophisticated multi-modal data stack including LiDAR and satellite imagery.
• Direct real-world impact by preventing wildfires and mitigating disaster risks.
• Strategic role with the ability to influence product features and company data direction.
• Competitive compensation package with a significant equity component.