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Camlin

Energy monitoring and infrastructure optimization

Data Scientist - Energy Analytics

Data ScienceUpdated on Nov 13
Full-timeParma, Province of Parma, ItalyNo salary listedIn-person

About the Job

Requirements

  • A degree in Data Science, Computer Science, Engineering, Physics, Mathematics, or a related quantitative discipline is required.
  • Experience in data science, advanced analytics, or a closely related technical role is required.
  • Strong programming skills in Python and SQL are required.
  • Experience analysing complex datasets, ideally including sensor, time-series, or operational data, is required.
  • Ability to translate real-world engineering concepts or domain knowledge into analytical models, calculations, and reusable logic is required.
  • A good understanding of statistical methods and quantitative problem-solving is required.
  • A structured approach to investigating data, testing assumptions, and validating analytical results is required.
  • Ability to work effectively with engineering and domain experts and communicate technical concepts clearly is required.

Responsibilities

  • Work with engineering and domain experts to understand electrical assets, their components, relationships, operating conditions, and behaviour.
  • Translate engineering knowledge into analytical models, calculations, rules, indicators, and derived measurements.
  • Analyse sensor, time-series, telemetry, and operational data from electrical infrastructure and energy networks.
  • Develop analytical solutions using Python and SQL, including data transformations, feature engineering, and calculation logic.
  • Develop methods to assess asset condition, performance, and behaviour, identifying anomalies and meaningful changes in operating patterns.
  • Apply statistical methods, anomaly detection, forecasting, and machine learning where they provide meaningful value.
  • Validate analytical outputs against engineering principles, domain knowledge, and available evidence, investigating data quality issues and unexpected results.
  • Develop analytical methods and take ownership of their implementation, validation, and documentation.
  • Collaborate with data engineering, domain experts, and software engineering teams to integrate analytical capabilities into customer-facing products.

Desired Qualifications

  • Experience in the energy sector, particularly electrical networks, power systems, or electrical infrastructure.
  • Knowledge of electrical assets such as transformers, switchgear, substations, or overhead lines.
  • Experience with asset monitoring, condition assessment, asset performance, or predictive maintenance.
  • Experience working with sensor measurements, telemetry, and time-series data.
  • Experience with anomaly detection, forecasting, machine learning, or engineering-based analytical models.
  • Experience developing analytical capabilities that are integrated into software products.
  • For senior-level candidates, experience developing analytical approaches to complex and sometimes ambiguous problems.
  • For senior-level candidates, ability to take ownership of analytical solutions from problem definition through to implementation and validation.
  • For senior-level candidates, experience designing robust, reusable analytical methods and making sound technical decisions.

About the Company

Camlin

Energy monitoring and infrastructure optimization

Camlin provides advanced energy monitoring and management solutions to optimize infrastructure and improve returns for energy operators. The company uses technologies such as artificial intelligence, machine learning, robotics, and materials science to address challenges in the energy sector, with a focus on Distribution Network Operators (DNOs). Its products include smart monitoring systems and fault detection and management strategies, delivered alongside related services. Revenue comes from selling these monitoring systems and ongoing services that help clients achieve higher operational efficiency and reliability of their networks. Camlin differentiates itself through a global team of data scientists, researchers, and engineers who continuously advance its solutions, aiming to improve customer outcomes and maximize the efficiency and reliability of energy networks.

Company size
201-500
Company stage
Grant
Total funding
$420K
Headquarters
Lisburn, United Kingdom
Founded
2011

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