Asset Analytics Engineer @ Capgemini Polska Sp. z o.o.

Capgemini Polska Sp. z o.o.; Poland; Hybrid; PLN 150,000 - 230,000; Full time

Benefits offered by this job

Medical care

Private life insurance

Wellbeing resources

Hybrid work model

Ergonomic home office package

Job summary

Capgemini Polska Sp. z o.o. is seeking an Asset Analytics Engineer focused on SmartSignal and predictive modelling to own the end-to-end technical deployment of models across industrial asset fleets. You will transform raw historian data into high-fidelity digital twins powering reliability decisions.

You will leverage platforms such as SmartSignal (GE Vernova), Aspen Mtell, or AVEVA PRiSM, and apply data science techniques in a hybrid work environment.

Qualifications

• Hands-on experience with platforms such as SmartSignal, Aspen Mtell, or AVEVA PRiSM and related blueprint/model-review workflows.

Responsibilities

• Own end-to-end deployment of predictive models across industrial asset fleets.
• Transform raw historian data into high-fidelity digital twins that inform reliability decisions.
• Maintain data quality and governance across model lifecycles, including training and retraining.

Skills

Python

SQL

Pandas

NumPy

Tools

SmartSignal

Aspen Mtell

AVEVA PRiSM

PI

OPC

IP21

Job description

Your profile

• 5+ years of experiencein data analytics, reliability engineering, or a related field, with hands-on experience on platforms such as SmartSignal, Aspen Mtell, or AVEVA PRiSM, including Blueprint and model review workflows
• StrongPython proficiency(Pandas, NumPy) for data manipulation and custom analytics development, combined with solidSQL skillsfor querying CMMS systems (Maximo, SAP PM) and Historian database
• Demonstrated experience withindustrial data systemsincluding PI, OPC, and IP21 historians, and familiarity with API data extraction tools such as Postman or equivalent
• A structured, detail-oriented approach todata quality and model governance, with the ability to manage model lifecycle activities including training, tuning, retraining, and performance monitoring across large asset fleets

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s mostinnovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as theyprovide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days arethe same.

Your role

As anAsset Analytics Engineerwith a focus on Smart Signal and Predictive Modelling, you will take ownership of the end-to-end technical deployment of predictive models across industrial asset fleets. Leveraging platforms such as SmartSignal (GE Vernova), Aspen Mtell, or AVEVA PRiSM, you will transform raw historian data into high-fidelity digital twins that power reliability decisions.

What You'll love about working here

• Well-being culture:medical care with Medicover, private life insurance, and sports card. But we went one step further by creating our own Capgemini Helpline offering therapeutical support if needed and the educational podcast "Let's talk about wellbeing" which you can listen to on Spotify.
• Access to over 70 training trackswith certification opportunities (e.g., GenAI, Architects, Google) on our NEXT platform. Dive into a world of knowledge with free access to Education First languages platform, TED Talks and Udemy Business materials and trainings.
• Continuous feedback and ongoing performance discussionsthanks to our performance management tool GetSuccess supported by a transparent performance management policy.
• Enjoy hybrid working modelthat fits your life - after completing onboarding, connect work from a modern office with ergonomic work from home, thanks to home office package (including laptop, monitor, and chair).

Get to know us

Capgemini is committed to diversity and inclusion, ensuring fairness in all employment practices. We evaluate individuals based on qualifications and performance, not personal characteristics, striving to create a workplace where everyone can succeed and feel valued.

About Capgemini

Capgemini is the business transformation partner for enterprises in the age of AI. We help organizations imagine and build an intelligent, sustainable future, combining AI, technology and human ingenuity to transform how they operate, innovate and grow. With unique end-to-end capabilities spanning strategy, technology, engineering and intelligent operations, we bring together deep industry expertise and market-leading capabilities in AI, cloud and data to turn ambition into measurable business outcomes at scale. Supported by a robust ecosystem of partners and nearly 60 years of expertise, Capgemini is a responsible and diverse global organization of over 410,000 team members in more than 50 countries. The Group reported 2025 revenues of €22.5 billion.

• Performing complextag mappingof historian data sources (PI, OPC, IP21) to the SmartSignal Standard Data Model, ensuring data lineage, quality, and consistency across fleet-level deployment, ApplyingSimilarity-Based Modelling (SBM)andEmpirical Model Learning (EML)techniques to establish accurate "Normal" operating profiles, selecting Gold Standard training windows that represent healthy asset state, Developing and maintainingAnalytic Blueprints- reusable templates for common industrial asset classes such as pumps, motors, and transformers - to enable rapid and scalable deployment, Monitoring model performance usingPrecision/Recall metrics, performing retraining following asset overhauls, and tuning statistical thresholds to minimise false positives and maximise signal fidelity, WritingPython scripts(Pandas, NumPy) for data manipulation, custom analytic rule development, and feature engineering to enhance model accuracy

Requirements: Data analytics, Python, pandas, NumPy, SQL, SAP, PM, API, Postman Additionally: Training budget, Sport subscription, Private healthcare, International projects, Free coffee, Bike parking, Free parking, Mobile phone, In-house trainings, Modern office, No dress code.