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Lyten

Develops 3D graphene-based energy solutions

Data Analyst

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeGdańsk, PolandNo salary listedIn-person

About the Job

Requirements

  • At least 2 years of experience in a data analysis role; experience in energy, battery, or Internet of Things domains is preferred.
  • Proficiency in Python, pandas, PyTorch or TensorFlow, SQL, and time-series analysis.
  • Proficiency with Tableau, Power BI, or Plotly/Dash.
  • Understanding of lithium-ion chemistry, battery management systems, or renewable integration.
  • Experience with regression models, neural networks, survival analysis, or reinforcement learning.
  • A minimum of a Bachelor's degree in Data Science, Statistics, Physics, or a related field.

Responsibilities

  • Analyze high-volume battery telemetry streams.
  • Build predictive maintenance models using machine learning techniques including regression, classification, and time-series forecasting.
  • Develop anomaly detection systems for early failure detection.
  • Create automated dashboards for operational teams and stakeholders.
  • Collaborate with engineering teams to translate insights into actionable recommendations.
  • Conduct root cause analysis on cell and module performance deviations.
  • Document methodologies and maintain reproducible analysis pipelines.

Desired Qualifications

  • Experience in energy, battery, or Internet of Things domains.

About the Company

Lyten

Develops 3D graphene-based energy solutions

Lyten develops and applies 3D graphene materials to help heavy-emitting industries reduce their carbon emissions. It builds applications on a materials platform centered on 3D graphene and is advancing Lithium-Sulfur batteries to improve EV efficiency and affordability. It differentiates itself by partnering with Fortune 500 customers and building a scalable platform rather than relying on a single product, with support from strategic investors like FedEx, Stellantis, and Honeywell. Its goal is to help large emitters reach net-zero while preserving profitability and accelerate the global transition to clean energy through practical, scalable technology.

Company size
501-1,000
Company stage
Late Stage VC
Total funding
$1.2B
Headquarters
San Jose, CA
Founded
2015

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