Sr Advanced Software Engr

Honeywell
Bengaluru
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningExperience: 8-12 yearsSkills: ["Communication","Collaboration","Analytical thinking","Problem-solving"]

Apply refinery/petrochemical process engineering expertise to analyze plant operations data and build analytics and machine learning solutions. You’ll work with structured and unstructured datasets (historian, lab, operations, equipment), detect trends/anomalies, and use Python for cleaning, transformation, visualization, and prototype development. Partner across operations, process engineering, data science, and software teams to translate domain knowledge into deployable ML capabilities and improve process performance, reliability, and operational efficiency.

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FursaFursa
Honeywell
Honeywell
4 days ago

Sr Advanced Software Engr

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Source: Company careers pageValidated by: Fursa AI
Last checked: 14 hours agoStatus: Live

Job Summary

Apply refinery/petrochemical process engineering expertise to analyze plant operations data and build analytics and machine learning solutions. You’ll work with structured and unstructured datasets (historian, lab, operations, equipment), detect trends/anomalies, and use Python for cleaning, transformation, visualization, and prototype development. Partner across operations, process engineering, data science, and software teams to translate domain knowledge into deployable ML capabilities and improve process performance, reliability, and operational efficiency.
Location: Bengaluru
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Analyze refinery/petrochemical process data to identify performance gaps, operating trends, deviations, and improvement opportunities.
  • •Work with structured and unstructured plant data from historians, laboratories, operations, and equipment datasets.
  • •Find patterns, correlations, anomalies, and early indicators in large volumes of operational and process data.
  • •Apply statistical analysis and machine learning techniques to solve practical process engineering and operational problems.
  • •Translate process engineering knowledge into analytical requirements, features, rules, and validation criteria for data science and software teams, supporting deployable analytics and ML platforms.

Key Requirements

  • •8–12 years of process engineering experience in refinery/petrochemical or closely related process-industry environments.
  • •Strong knowledge of refinery/petrochemical process units, plant operations, process control, safety systems, and real-time operating data.
  • •Hands-on Python skills for data analysis, automation, visualization, and prototype development; production software engineering experience is a plus.
  • •Experience with data analysis libraries such as Pandas and NumPy for engineering and operational datasets.
  • •Experience with statistical analysis and ML use cases (e.g., soft sensors, predictive monitoring, fault detection, optimization, reliability analytics), plus the ability to validate outputs using process engineering judgment.
Experience:8-12 yearsRefineryPetrochemicalsProcess industryIndustrial automationIndustrial data
Skills:CommunicationCollaborationAnalytical thinkingProblem-solving
Languages:English
Tech Stack:PythonMachine learningPandasNumPySQLPySparkCI/CDDevOpsDCSPLCProcess historiansP&IDsPFDsData analysisData visualizationAnomaly detectionFeature engineeringTrend analysis

Company Brief

Honeywell
Global diversified technology and manufacturing company providing aerospace systems, building technologies, performance materials, and safety & productivity solutions for industrial, commercial, and consumer markets.
Industry: Conglomerates & Holding Companies
Company Size: Enterprise (1,001+ employees)
Revenue: USD 25B to 50B
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Charlotte, United States
Founded: 1906
Glassdoor
Glassdoor: 3.8
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