106 Predictive Analytics jobs in India

Responsibilities

• Implement Asset Predictive Analytics (APA) (Utilizing software packages such as AVEVA or Smart Signal or its equivalent) for major rotating and static equipment such as compressors and pumps with large prime movers (- gas turbines, steam turbines & motors), Blowers, fans, fired heaters, distillation columns, Transformers, Heat exchangers (including cryogenics).
• Conduct Data Collection and Analysis including:
• Gathering data from various sources, including sensors, maintenance logs, and operational data,
• Cleaning, validating, and preparing data for analysis,
• Developing and implementing data quality control processes,
• Analyzing data to identify trends, patterns, and anomalies related to equipment performance and potential failures.
• Conduct Predictive Modeling including:
• Developing and implementing predictive models using machine learning algorithms to forecast potential equipment failures,
• Evaluating the performance of predictive models and refining them over time,
• Integrating predictive models into existing systems and workflows.
• Conduct Maintenance Optimization including:
• Using predictive insights to optimize maintenance schedules and prevent unplanned downtime,
• Recommending maintenance strategies based on predicted failure risks,
• Collaborating with maintenance teams to implement optimized maintenance plans.

Qualifications

• B.E/B.Tech (Mechanical/Chemical Engineering) or equivalent degree from recognized university.
• Minimum 5+ plus years’ experience in APA in industrial sectors (preferred oil & gas).

Required Skills

• Knowledge of reliability principles, tools, and methodologies (e.g., FMEA, RCFA, RCM, PMO).
• Rich Experience in AVEVA Predictive Analytics or similar solutions.
• Strong understanding of mechanical systems and equipment.
• Proficiency in data analysis and statistical modeling, including statistical modeling, machine learning algorithms, and data visualization.
• Proficiency in programming languages such as Python, R, or others commonly used for data analysis and machine learning.
• Experience developing and implementing predictive models using machine learning algorithms, such as regression, classification, and time series analysis.
• Ability to effectively communicate technical information to both technical and non-technical audiences.
• Experience with CMMS (Computerized Maintenance Management System), SCADA (Supervisory Control and Data Acquisition), and other relevant software and tools.
• Rotating machinery Fault Analysis.
• Static equipment Fault analysis.
• Ability to engage with client/team stakeholders at a senior level.

Responsibilities

• Implement Asset Predictive Analytics (APA) (Utilizing software packages such as AVEVA or Smart Signal or its equivalent) for major rotating and static equipment such as compressors and pumps with large prime movers (- gas turbines, steam turbines & motors), Blowers, fans, fired heaters, distillation columns, Transformers, Heat exchangers (including cryogenics).
• Conduct Data Collection and Analysis including:
• Gathering data from various sources, including sensors, maintenance logs, and operational data,
• Cleaning, validating, and preparing data for analysis,
• Developing and implementing data quality control processes,
• Analyzing data to identify trends, patterns, and anomalies related to equipment performance and potential failures.
• Conduct Predictive Modeling including:
• Developing and implementing predictive models using machine learning algorithms to forecast potential equipment failures,
• Evaluating the performance of predictive models and refining them over time,
• Integrating predictive models into existing systems and workflows.
• Conduct Maintenance Optimization including:
• Using predictive insights to optimize maintenance schedules and prevent unplanned downtime,
• Recommending maintenance strategies based on predicted failure risks,
• Collaborating with maintenance teams to implement optimized maintenance plans.

Qualifications

• B.E/B.Tech (Mechanical/Chemical Engineering) or equivalent degree from recognized university.
• Minimum 5+ plus years’ experience in APA in industrial sectors (preferred oil & gas).

Required Skills

• Knowledge of reliability principles, tools, and methodologies (e.g., FMEA, RCFA, RCM, PMO).
• Rich Experience in AVEVA Predictive Analytics or similar solutions.
• Strong understanding of mechanical systems and equipment.
• Proficiency in data analysis and statistical modeling, including statistical modeling, machine learning algorithms, and data visualization.
• Proficiency in programming languages such as Python, R, or others commonly used for data analysis and machine learning.
• Experience developing and implementing predictive models using machine learning algorithms, such as regression, classification, and time series analysis.
• Ability to effectively communicate technical information to both technical and non-technical audiences.
• Experience with CMMS (Computerized Maintenance Management System), SCADA (Supervisory Control and Data Acquisition), and other relevant software and tools.
• Rotating machinery Fault Analysis.
• Static equipment Fault analysis.
• Ability to engage with client/team stakeholders at a senior level.

Responsibilities

• Implement Asset Predictive Analytics (APA) (Utilizing software packages such as AVEVA or Smart Signal or its equivalent) for major rotating and static equipment such as compressors and pumps with large prime movers (- gas turbines, steam turbines & motors), Blowers, fans, fired heaters, distillation columns, Transformers, Heat exchangers (including cryogenics).
• Conduct Data Collection and Analysis including:
• Gathering data from various sources, including sensors, maintenance logs, and operational data,
• Cleaning, validating, and preparing data for analysis,
• Developing and implementing data quality control processes,
• Analyzing data to identify trends, patterns, and anomalies related to equipment performance and potential failures.
• Conduct Predictive Modeling including:
• Developing and implementing predictive models using machine learning algorithms to forecast potential equipment failures,
• Evaluating the performance of predictive models and refining them over time,
• Integrating predictive models into existing systems and workflows.
• Conduct Maintenance Optimization including:
• Using predictive insights to optimize maintenance schedules and prevent unplanned downtime,
• Recommending maintenance strategies based on predicted failure risks,
• Collaborating with maintenance teams to implement optimized maintenance plans.

Qualifications

• B.E/B.Tech (Mechanical/Chemical Engineering) or equivalent degree from recognized university.
• Minimum 5+ plus years’ experience in APA in industrial sectors (preferred oil & gas).

Required Skills

• Knowledge of reliability principles, tools, and methodologies (e.g., FMEA, RCFA, RCM, PMO).
• Rich Experience in AVEVA Predictive Analytics or similar solutions.
• Strong understanding of mechanical systems and equipment.
• Proficiency in data analysis and statistical modeling, including statistical modeling, machine learning algorithms, and data visualization.
• Proficiency in programming languages such as Python, R, or others commonly used for data analysis and machine learning.
• Experience developing and implementing predictive models using machine learning algorithms, such as regression, classification, and time series analysis.
• Ability to effectively communicate technical information to both technical and non-technical audiences.
• Experience with CMMS (Computerized Maintenance Management System), SCADA (Supervisory Control and Data Acquisition), and other relevant software and tools.
• Rotating machinery Fault Analysis.
• Static equipment Fault analysis.
• Ability to engage with client/team stakeholders at a senior level.

Responsibilities

• Implement Asset Predictive Analytics (APA) (Utilizing software packages such as AVEVA or Smart Signal or its equivalent) for major rotating and static equipment such as compressors and pumps with large prime movers (- gas turbines, steam turbines & motors), Blowers, fans, fired heaters, distillation columns, Transformers, Heat exchangers (including cryogenics).
• Conduct Data Collection and Analysis including:
• Gathering data from various sources, including sensors, maintenance logs, and operational data,
• Cleaning, validating, and preparing data for analysis,
• Developing and implementing data quality control processes,
• Analyzing data to identify trends, patterns, and anomalies related to equipment performance and potential failures.
• Conduct Predictive Modeling including:
• Developing and implementing predictive models using machine learning algorithms to forecast potential equipment failures,
• Evaluating the performance of predictive models and refining them over time,
• Integrating predictive models into existing systems and workflows.
• Conduct Maintenance Optimization including:
• Using predictive insights to optimize maintenance schedules and prevent unplanned downtime,
• Recommending maintenance strategies based on predicted failure risks,
• Collaborating with maintenance teams to implement optimized maintenance plans.

Qualifications

• B.E/B.Tech (Mechanical/Chemical Engineering) or equivalent degree from recognized university.
• Minimum 5+ plus years’ experience in APA in industrial sectors (preferred oil & gas).

Required Skills

• Knowledge of reliability principles, tools, and methodologies (e.g., FMEA, RCFA, RCM, PMO).
• Rich Experience in AVEVA Predictive Analytics or similar solutions.
• Strong understanding of mechanical systems and equipment.
• Proficiency in data analysis and statistical modeling, including statistical modeling, machine learning algorithms, and data visualization.
• Proficiency in programming languages such as Python, R, or others commonly used for data analysis and machine learning.
• Experience developing and implementing predictive models using machine learning algorithms, such as regression, classification, and time series analysis.
• Ability to effectively communicate technical information to both technical and non-technical audiences.
• Experience with CMMS (Computerized Maintenance Management System), SCADA (Supervisory Control and Data Acquisition), and other relevant software and tools.
• Rotating machinery Fault Analysis.
• Static equipment Fault analysis.
• Ability to engage with client/team stakeholders at a senior level.

Responsibilities

• Implement Asset Predictive Analytics (APA) (Utilizing software packages such as AVEVA or Smart Signal or its equivalent) for major rotating and static equipment such as compressors and pumps with large prime movers (- gas turbines, steam turbines & motors), Blowers, fans, fired heaters, distillation columns, Transformers, Heat exchangers (including cryogenics).
• Conduct Data Collection and Analysis including:
• Gathering data from various sources, including sensors, maintenance logs, and operational data,
• Cleaning, validating, and preparing data for analysis,
• Developing and implementing data quality control processes,
• Analyzing data to identify trends, patterns, and anomalies related to equipment performance and potential failures.
• Conduct Predictive Modeling including:
• Developing and implementing predictive models using machine learning algorithms to forecast potential equipment failures,
• Evaluating the performance of predictive models and refining them over time,
• Integrating predictive models into existing systems and workflows.
• Conduct Maintenance Optimization including:
• Using predictive insights to optimize maintenance schedules and prevent unplanned downtime,
• Recommending maintenance strategies based on predicted failure risks,
• Collaborating with maintenance teams to implement optimized maintenance plans.

Qualifications

• B.E/B.Tech (Mechanical/Chemical Engineering) or equivalent degree from recognized university.
• Minimum 5+ plus years’ experience in APA in industrial sectors (preferred oil & gas).

Required Skills

• Knowledge of reliability principles, tools, and methodologies (e.g., FMEA, RCFA, RCM, PMO).
• Rich Experience in AVEVA Predictive Analytics or similar solutions.
• Strong understanding of mechanical systems and equipment.
• Proficiency in data analysis and statistical modeling, including statistical modeling, machine learning algorithms, and data visualization.
• Proficiency in programming languages such as Python, R, or others commonly used for data analysis and machine learning.
• Experience developing and implementing predictive models using machine learning algorithms, such as regression, classification, and time series analysis.
• Ability to effectively communicate technical information to both technical and non-technical audiences.
• Experience with CMMS (Computerized Maintenance Management System), SCADA (Supervisory Control and Data Acquisition), and other relevant software and tools.
• Rotating machinery Fault Analysis.
• Static equipment Fault analysis.
• Ability to engage with client/team stakeholders at a senior level.

• Assist in data collection, cleaning, and preprocessing from various sources.
• Develop and implement basic predictive models under supervision.
• Perform exploratory data analysis (EDA) to identify patterns and trends.
• Contribute to feature engineering and selection for machine learning models.
• Evaluate model performance and assist in hyperparameter tuning.
• Create data visualizations to communicate findings effectively.
• Collaborate with senior data scientists on ongoing projects.
• Learn and apply various statistical and machine learning techniques.
• Document code and methodologies clearly.
• Participate in team meetings and contribute to discussions.

• Currently pursuing or recently completed a Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
• Foundational understanding of statistics, probability, and machine learning concepts.
• Proficiency in Python or R for data analysis and manipulation (e.g., Pandas, NumPy).
• Familiarity with data visualization libraries (e.g., Matplotlib, Seaborn, Plotly).
• Basic knowledge of SQL for data querying.
• Strong analytical and problem-solving abilities.
• Excellent communication skills, both written and verbal.
• Eagerness to learn and adapt to new technologies.
• Ability to work independently and as part of a remote team.

• Develop and deploy predictive models using machine learning algorithms.
• Analyze large, complex datasets to identify trends and insights.
• Clean, preprocess, and transform data for modeling.
• Evaluate and validate model performance.
• Communicate findings and recommendations to stakeholders.
• Collaborate with business units to understand data needs.
• Design and conduct A/B tests and experiments.
• Stay updated with the latest data science techniques.
• Mentor junior data scientists and analysts.
• Build data pipelines and automate analytical processes.
• Create data visualizations to present insights effectively.
• Contribute to the development of data strategies.
• Identify opportunities for data-driven improvements.
• Ensure data quality and integrity throughout the analytical process.
• Explore and implement new tools and technologies for data analysis.