Neara Logo

Neara

Data Scientist

Reposted 2 Hours Ago
Hybrid
New York City, NY, USA
160K-190K Annually
Mid level
Hybrid
New York City, NY, USA
160K-190K Annually
Mid level
Analyze multimodal geospatial and infrastructure data to build physics-enabled digital twin models of electric grids. Develop AI and machine learning models, metrics, experiments, and scalable data pipelines; QA predictive models and identify data-quality issues. Translate findings into deployable software and product features, advise leadership and customers, and mentor others on modeling and analytics best practices.
The summary above was generated by AI

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.

Data Scientist

As a Data Scientist, you will analyze a rich array of real-world data to inform our digital twin model of the electric grid, including topography, LIDAR, imagery, vegetation, structural loading, and electrical connectivity. Your work will drive product direction with high visibility, highlight grid expansion opportunities, identify aging and risky infrastructure, and help our customers understand where to build and invest. Working alongside ML Engineers and product-facing engineering teams, your ideas will ultimately take shape as new product features that expand what Neara is capable of doing, and as new infrastructure buildouts for the energy grid itself.

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, 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, PostgreSQL, Spark, and DynamoDB.

  • 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.

#LI-NT1 #LI-DNP

Similar Jobs

9 Hours Ago
Hybrid
New York, NY, USA
197K-246K Annually
Senior level
197K-246K Annually
Senior level
Fintech • Machine Learning • Payments • Software • Financial Services
Leads data science for credit card acquisition decisioning, including systemic risk monitoring, statistical analysis, vulnerability detection, and multi-model infrastructure. Builds LLM and Agentic AI solutions, develops machine learning models, analyzes large-scale data, and partners with data scientists, analysts, and software engineers. Translates complex technical findings into business goals while guiding innovation and talent development.
Top Skills: Agentic AiAWSLarge Language ModelsMachine LearningPythonRRelational DatabasesScalaSQL
Yesterday
Hybrid
2 Locations
99K-232K Annually
Senior level
99K-232K Annually
Senior level
Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
Leads teams in designing and deploying scalable AI and machine learning solutions for consulting clients. Responsibilities include data wrangling, complex analysis, data modeling, AI system implementation, data pipeline and infrastructure oversight, deep learning, neural networks, data quality validation, and stakeholder collaboration. The manager coaches team members, manages performance, supports innovation, and applies Python, Java, and cloud technologies to build production-ready AI applications.
Top Skills: AWSCloud PlatformsData PipelinesDatabricksDeep LearningGCPJavaMachine Learning LibrariesAzureNatural Language Processing (Nlp)Neural NetworksPythonSnowflake
2 Days Ago
In-Office
New York, NY, USA
150K-190K Annually
Mid level
150K-190K Annually
Mid level
Artificial Intelligence • Fintech • Financial Services
Build and deploy data science models for CPG brands, focusing on demand and sales forecasting, promotion effectiveness, pricing, elasticity, and cannibalization. Analyze messy retail, inventory, trade promotion, and supply-chain data; develop statistical validation and evaluation methods; and communicate model insights and uncertainty to technical and non-technical stakeholders. Collaborate with AI/ML engineers to move analyses into production.
Top Skills: AWSDbtPythonSnowflakeSQL

What you need to know about the NYC Tech Scene

As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.

Key Facts About NYC Tech

  • Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
  • Key Industries: Artificial intelligence, Fintech
  • Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
  • Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account