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Data Scientist

Job in New York, New York County, New York, 10261, USA
Listing for: AI Chopping Block, Inc.
Full Time position
Listed on 2026-06-05
Job specializations:
  • IT/Tech
    Data Engineer, Data Scientist
Salary/Wage Range or Industry Benchmark: 100000 - 125000 USD Yearly USD 100000.00 125000.00 YEAR
Job Description & How to Apply Below
Location: New York

Data Scientist

Imagine having the power to stress-test an entire power grid against a hurricane or thunderstorm before the clouds even gather. That is the reality we are creating at Neara.

We use advanced machine learning to create engineering-grade, physics enabled digital twins of electricity grids across four continents, this helps asset owners understand their biggest challenges and bring the most viable solutions to life across millions of kilometres of infrastructure.

By simulating extreme weather and structural stress at a network-wide scale, we empower the world’s largest utilities to pinpoint risks, optimise investments and build a more resilient global energy future.

Our team is a collection of brilliant minds who are fanatical about making a tangible difference in the real world, utilising AI and machine learning to accelerate everything from data classification to complex scenario analysis. We have built a special culture where innovation thrives because everyone owns the mission and we need smart, creative people to help us scale this impact to every corner of the globe.

What You Will Do:
  • Model accurate digital twin electric networks from imperfect data using AI, deep learning, and classical ML algorithms.

  • Surface meaningful analytics and metrics such as wildfire risk that help guide customer buildout of electrical infrastructure.

  • Advise the company on what our data says and use that understanding to inform Neara’s strategy.

  • Conduct experiments and A/B tests to improve our modeling of the grid.

  • QA and improve our predictive models; identify data issues such as distribution drift, overfitting, or test set leakage.

  • Craft scalable data pipelines to work with a variety of data sources, including LiDAR, aerial photography, photogrammetry and GIS.

  • Mentor others in best practices for model training, data analytics, and building data-driven products.

Who You Are:
  • A data scientist, ML scientist, data engineer, or similar with 3-6 years of experience at technical, data-driven companies operating in complex environments. Geospatial data or power grid experience are a plus.

  • You have a strong intuition for data with good communication skills and experience sharing your findings with customers and senior leaders.

  • Demonstrated experience with AI and Machine Learning and a keen intuition for data modeling.

  • Experience translating your models into both experiments and deployable software.

  • Proficiency in data storage and ETL technologies, such as Parquet, Databricks, Snowflake, Postgre

    SQL, Spark, and Dynamo

    DB.

  • Comfort working in an AWS cloud environment.

  • Excellent problem-solving skills as applied to new domains.

  • Ability to work effectively asynchronously and cross-functionally on novel, cutting-edge problems.

  • Ability to own problems and proactively approach challenges.

  • Prior experience in the energy industry is a plus.

What We Offer:
  • Work with a sophisticated, multi-modal data stack, including LiDAR, satellite imagery, and physics-enabled digital twins, to solve high-stakes engineering problems that most data scientists only see in theory.

  • Your models will directly prevent wildfires and mitigate disaster risks across millions of kilometers of infrastructure, moving beyond "digital metrics" to harden the real-world energy grid.

  • You won't just build models; you’ll advise the company on data strategy and see your experiments evolve into core product features that dictate how the world’s largest utilities invest.

  • We offer a highly competitive compensation package with a significant equity component, ensuring you are a true stakeholder in our mission and benefit directly from the company’s rapid global scale.

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