Predictive Asset Analytics Engineer

Capgemini Engineering; Katowice; Hybrid; PLN 150,000 - 190,000; Full time

Benefits offered by this job

Medicover medical care

Private life insurance

Sports card

Capgemini Helpline for wellbeing

Training tracks on NEXT platform

GetSuccess performance management tool

Hybrid working model

Home office package

Job summary

Capgemini Engineering in Katowice seeks an Asset Analytics Engineer to deploy predictive models across industrial asset fleets, turning historian data into digital twins to support reliability decisions and scalable deployments.

You will work with SmartSignal, Aspen Mtell, or AVEVA PRiSM, leveraging Python (Pandas, NumPy) and SQL, and handling data quality and model governance across large fleets.

Qualifications

• 5+ years of experience in 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.
• Strong Python proficiency (Pandas, NumPy) for data manipulation and custom analytics development, combined with solid SQL skills for querying CMMS systems (Maximo, SAP PM) and Historian database.
• Demonstrated experience with industrial data systems including PI, OPC, and IP21 historians, and familiarity with API data extraction tools such as Postman or equivalent.
• A structured, detail-oriented approach to data quality and model governance, with the ability to manage model lifecycle activities including training, tuning, retraining, and performance monitoring across large asset fleets.

Responsibilities

• Performing complete tag mapping of historian data sources (PI, OPC, IP21) to the SmartSignal Standard Data Model, ensuring data lineage, quality, and consistency across fleet-level deployment.
• Applying SBM and EML techniques to establish accurate 'Normal' operating profiles, selecting Gold Standard training windows that represent healthy asset state.
• Developing and maintaining Analytic Blueprints for pumps, motors, and transformers to enable rapid and scalable deployment.
• Monitoring model performance using precision/recall metrics, retraining after asset overhauls, and tuning thresholds to minimise false positives and maximise signal fidelity.
• Writing Python scripts (Pandas, NumPy) for data manipulation, custom analytic rule development, and feature engineering to enhance model accuracy.

Skills

Python (Pandas, NumPy)

SQL

PI/OPC/IP21 historian data

Postman/API data extraction

Data analytics

Tools

SmartSignal

Aspen Mtell

AVEVA PRiSM

Job description

Capgemini Engineering in Katowice seeks an Asset Analytics Engineer to deploy predictive models across industrial asset fleets, turning historian data into digital twins to support reliability decisions and scalable deployments.

You will work with SmartSignal, Aspen Mtell, or AVEVA PRiSM, leveraging Python (Pandas, NumPy) and SQL, and handling data quality and model governance across large fleets.