9,302 Senior Data Science Analysts 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 10+ 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 10+ 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 10+ 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.

• Developing and implementing sophisticated predictive models using machine learning and statistical techniques.
• Designing and executing experiments to test hypotheses and evaluate model performance.
• Analyzing large and complex datasets to identify patterns, trends, and anomalies.
• Collaborating with data engineers to build robust data pipelines and ensure data quality.
• Translating business requirements into data science problems and solutions.
• Communicating complex analytical findings and recommendations to both technical and non-technical audiences.
• Mentoring junior data scientists and contributing to the team's technical growth.
• Staying current with the latest research and advancements in data science, machine learning, and AI.
• Building and maintaining production-ready machine learning models.
• Ensuring compliance with data privacy and security regulations.
• Contributing to the development of the company's data strategy and roadmap.

• Assist in data collection, cleaning, and pre-processing from various sources.
• Perform exploratory data analysis (EDA) to uncover trends and patterns.
• Support the development and implementation of machine learning models (classification, regression, clustering).
• Contribute to feature engineering and model selection processes.
• Evaluate model performance and interpret results.
• Create data visualizations and reports to communicate findings effectively.
• Collaborate with senior data scientists and engineers on project tasks.
• Participate in code reviews and team meetings.
• Learn and apply new data science techniques and tools.
• Document analytical processes and code.

• Currently pursuing or recently completed a Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
• Strong understanding of statistical concepts and their application.
• Proficiency in at least one programming language (Python preferred) and relevant libraries (Pandas, NumPy, Scikit-learn).
• Familiarity with machine learning algorithms and concepts.
• Basic knowledge of SQL and database querying.
• Excellent analytical and problem-solving abilities.
• Good written and verbal communication skills.
• Ability to work independently and as part of a remote team.

• Assist in data collection, cleaning, and pre-processing from various sources.
• Support the development and implementation of machine learning models for predictive tasks.
• Perform exploratory data analysis (EDA) to identify patterns, trends, and anomalies in datasets.
• Help in evaluating model performance and documenting findings.
• Collaborate with senior data scientists and domain experts to understand project requirements and deliver insights.
• Visualize data and model results using various tools and techniques.
• Contribute to the maintenance and improvement of existing data pipelines and models.
• Participate in team meetings and present findings and progress.
• Learn and apply new data science techniques and tools as required by projects.

• Currently pursuing a Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
• Strong foundational knowledge of statistics, probability, and machine learning algorithms.
• Proficiency in programming languages such as Python or R, and relevant libraries (e.g., Pandas, NumPy, Scikit-learn).
• Familiarity with data visualization tools (e.g., Matplotlib, Seaborn, Tableau).
• Eagerness to learn and a proactive approach to problem-solving.
• Good communication skills, both written and verbal.
• Ability to work effectively in a team and independently.
• Understanding of SQL and database concepts is a plus.
• Enthusiasm for applying data science to solve business problems.

• Leading the design and implementation of machine learning and predictive models.
• Developing robust data pipelines for model training and deployment.
• Conducting in-depth exploratory data analysis to uncover trends and insights.
• Mentoring and guiding junior data scientists and analysts.
• Collaborating with business stakeholders to define analytical requirements and deliver solutions.
• Communicating complex analytical results and recommendations to senior management.
• Staying current with the latest advancements in data science and AI.
• Ensuring the ethical and responsible use of data.

• Ph.D. or Master's degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
• 7+ years of hands-on experience in data science and machine learning.
• Proficiency in programming languages such as Python or R, and libraries like TensorFlow, PyTorch, scikit-learn.
• Strong experience with SQL and big data technologies (e.g., Spark, Hadoop).
• Experience with cloud platforms (AWS, Azure, GCP) for data science workloads.
• Excellent problem-solving, communication, and presentation skills.
• Demonstrated experience in leading data science projects and teams.