{"id":3759699,"url":"https://alion.io/job/camlin-group-data-scientist-energy-analytics","title":"Data Scientist - Energy Analytics","company":{"id":696826,"name":"Camlin Group","domain":"camlingroup.com","url":"https://alion.io/company/camlingroup","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Rippling","truth_index":{"grade":"B","score":84,"open_postings":16,"ghost_share":0,"stale_share":0.625,"repost_share":0,"time_to_fill_p50_days":29,"computed_at":"2026-11-09T06:03:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Parma, Italy"],"countries":["IT"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anomaly Detection","optional":false},{"name":"Databricks","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Time Series","optional":false}],"status":"live","first_seen_at":"2026-11-04T15:34:48Z","employer_posted_date":"2026-11-04","last_verified_at":"2026-11-09T22:01:21Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"About Camlin\nCamlin is a global technology leader that operates with the vision of bringing revolutionary products to life for a wide range of industries, including power and rail, and also has interests in a number of R&D projects in a variety of scientific sectors.\nAt Camlin we believe in high quality engineering and design, allowing us to develop market leading products and services. In short, we love creating value for our customers by solving difficult problems. As of now, Camlin operates in over 20 countries worldwide.\nThe Role\nWe are looking for a Data Scientist to develop analytical models and intelligence for energy applications.\nWorking closely with engineering and domain experts, you will understand how electrical assets behave, what their measurements represent and how engineering knowledge can be translated into analytical models, calculations, rules and indicators.\nYou will work with complex sensor, time-series, telemetry and operational data, developing analytical methods that turn measurements into meaningful information about asset condition, performance and behaviour.\nWe are open to considering candidates at both mid-level and senior level, with the position and responsibilities reflecting the successful candidate's experience.\nTechnology Environment\nOur data and analytics environment includes Python, SQL, Apache Spark, PySpark, Databricks and MLflow, alongside other cloud-based data technologies.\nExperience with these platforms and technologies is advantageous. Strong underlying programming, analytical and problem-solving skills are more important than familiarity with any specific technology.\nWhat Makes This Role Different\nThis is not a traditional BI or reporting role, nor is it purely focused on developing machine learning models.\nThe key challenge is understanding what energy asset data represents, combining measurements with engineering knowledge, and translating that understanding into reliable analytical intelligence.\nYou will work on real engineering problems and help develop the analytical capabilities behind solutions used to monitor and understand critical energy infrastructure.\nKey Responsibilities\nWork with engineering and domain experts to understand electrical assets, their components, relationships, operating conditions and behaviour. \nTranslate engineering knowledge into analytical models, calculations, rules, indicators and derived measurements. \nAnalyse sensor, time-series, telemetry and operational data from electrical infrastructure and energy networks. \nDevelop analytical solutions using Python and SQL, including data transformations, feature engineering and calculation logic. \nDevelop methods to assess asset condition, performance and behaviour, identifying anomalies and meaningful changes in operating patterns. \nApply statistical methods, anomaly detection, forecasting and machine learning where they provide meaningful value. \nValidate analytical outputs against engineering principles, domain knowledge and available evidence, investigating data quality issues and unexpected results. \nDevelop analytical methods and take ownership of their implementation, validation, and documentation. \nCollaborate with data engineering, domain experts and software engineering teams to integrate analytical capabilities into customer-facing products. \nWhat We Are Looking For\nA degree in Data Science, Computer Science, Engineering, Physics, Mathematics or a related quantitative discipline. \nExperience in data science, advanced analytics or a closely related technical role. \nStrong programming skills in Python and SQL. \nExperience analysing complex datasets, ideally including sensor, time-series or operational data. \nAbility to translate real-world engineering concepts or domain knowledge into analytical models, calculations and reusable logic. \nGood understanding of statistical methods and quantitative problem-solving. \nA structured approach to investigating data, testing assumptions and validating analytical results. \nAbility to work effectively with engineering and domain experts and communicate technical concepts clearly. \nFor senior-level candidates, we would additionally expect:\nExperience developing analytical approaches to complex and sometimes ambiguous problems. \nAbility to take ownership of analytical solutions from problem definition through to implementation and validation. \nExperience designing robust, reusable analytical methods and making sound technical decisions. \nNice to have\nExperience in the energy sector, particularly electrical networks, power systems or electrical infrastructure. \nKnowledge of electrical assets such as transformers, switchgear, substations or overhead lines. \nExperience with asset monitoring, condition assessment, asset performance or predictive maintenance. \nExperience working with sensor measurements, telemetry and time-series data. \nExperience with anomaly detection, forecasting, machine learning or engineering-based analytical models. \nExperience developing analytical capabilities that are integrated into software products.\nOur Values\nWe work together\nWe believe in people\nWe won’t accept the ‘way it has always been done’\nWe listen to learn\nWe’re trying to do the right thing\nEqual Employment Opportunity Statement\nIndividuals seeking employment at Camlin are considered without regards to race, colour, religion, national origin, age, sex, marital states, ancestry, physical or mental 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