9,168 Predictive Analytics jobs in India

Job Title:
Predictive Analytics Engineer / Reliability Engineer

location: Hyderabad (On-site / Work from Office)

Job Summary:

We are seeking a skilled and motivated professional with expertise in
Predictive Analytics
and
Maintenance Systems
to join our team. The ideal candidate will have hands-on experience with
APA
, industrial equipment monitoring, and strong technical skills in software and data tools. This role focuses on driving asset performance, improving reliability, and supporting proactive maintenance strategies through advanced analytics.

Key Responsibilities:

• Develop, deploy, and maintain predictive analytics models for industrial equipment using tools like
  APA
  ,
  PRiSM
  , and
  SmartSignal
  .
• Analyze equipment performance data to identify trends, patterns, and potential failure modes.
• Collaborate with maintenance and operations teams to optimize equipment uptime and reliability.
• Design and implement dashboards and reports using
  SQL
  ,
  SSRS
  , and
  MS Office
  tools.
• Write scripts and automation tools using
  C#
  ,
  .NET
  , and
  PowerShell
  to support analytics workflows.
• Integrate predictive analytics with existing maintenance systems and business processes.
• Provide technical support and training to stakeholders on analytics tools and insights.
• Stay up to date with the latest developments in predictive maintenance, industrial IoT, and reliability engineering.

Key Skills & Qualifications:

• Strong knowledge of
  Predictive Analytics
  and
  Condition-Based Monitoring
  .
• Experience working with
  APA
  ,
  PRiSM
  ,
  SmartSignal
  , or similar platforms.
• Familiarity with
  Maintenance Systems
  and reliability-centered maintenance practices.
• Understanding of
  Industrial Equipment
  and asset performance management.
• Proficiency in
  C#
  ,
  .NET
  ,
  PowerShell
  ,
  SQL
  , and
  SSRS
  .
• Advanced knowledge of
  MS Office
  , particularly Excel and PowerPoint.
• Strong analytical, problem-solving, and communication skills.
• Bachelor's or Master's degree in Engineering, Computer Science, Data Science, or a related field.

Preferred Qualifications:

• Experience in industrial environments such as Oil & Gas, Energy, Utilities, or Manufacturing.
• Knowledge of machine learning techniques applied to predictive maintenance.
• Familiarity with asset hierarchy, data historians, and SCADA systems.

• Assist senior data analysts in collecting, cleaning, and organizing large datasets from various sources.
• Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies.
• Support the development and validation of predictive models under the guidance of experienced team members.
• Generate reports and visualizations to communicate findings and insights to stakeholders.
• Contribute to data quality assurance and integrity checks.
• Learn and apply various data analysis tools and techniques, including statistical methods and machine learning algorithms.
• Collaborate with team members on data-related projects and initiatives.
• Document data sources, methodologies, and findings clearly and concisely.
• Participate in team meetings and contribute ideas for improving data analysis processes.
• Gain practical experience in using SQL, Python/R, and data visualization tools (e.g., Tableau, Power BI).
• Support ad-hoc data requests from different departments.

• Currently pursuing or recently completed a Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Economics, or a related quantitative field.
• Foundational knowledge of statistical concepts and data analysis techniques.
• Basic proficiency in SQL for data querying.
• Familiarity with at least one programming language commonly used in data analysis, such as Python or R.
• Strong analytical and problem-solving skills with a keen attention to detail.
• Excellent communication and collaboration abilities.
• Eagerness to learn and adapt to new technologies and methodologies.
• Previous internship or project experience in data analysis is a plus.
• Ability to work effectively both independently and as part of a team.
• This is a hybrid role, requiring a mix of on-site work at our Thiruvananthapuram, Kerala, IN office and remote work.

• Design, develop, and implement advanced predictive models using machine learning and statistical techniques.
• Extract, clean, and transform large, complex datasets from various sources.
• Perform exploratory data analysis to identify trends, patterns, and insights.
• Validate and test model performance, ensuring accuracy and reliability.
• Deploy predictive models into production environments, collaborating with engineering teams.
• Communicate complex analytical findings and recommendations clearly to stakeholders at all levels.
• Stay abreast of the latest advancements in data science, machine learning, and artificial intelligence.
• Identify opportunities for leveraging data analytics to solve business problems and drive innovation.
• Collaborate with cross-functional teams to define project requirements and analytical approaches.
• Mentor junior data scientists and contribute to the development of data science best practices.

• Master's or Ph.D. in Statistics, Computer Science, Mathematics, Economics, or a related quantitative field.
• 5+ years of experience in data science, with a strong focus on predictive modeling and analytics.
• Proficiency in Python or R, and experience with relevant data science libraries (e.g., scikit-learn, TensorFlow, PyTorch, statsmodels).
• Expertise in SQL and experience with big data technologies (e.g., Spark, Hadoop) is highly desirable.
• Strong understanding of various machine learning algorithms (regression, classification, clustering, time series analysis).
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and presentation skills, with the ability to explain complex concepts to diverse audiences.
• Experience working in a hybrid environment, collaborating effectively both in-person and remotely.
• Proven ability to translate business needs into data science solutions.

• Develop and deploy advanced predictive models using machine learning and statistical techniques.
• Analyze large, complex datasets to identify patterns and trends.
• Translate business problems into data science solutions.
• Design and execute experiments to test hypotheses and validate models.
• Interpret model results and communicate insights to stakeholders.
• Clean, transform, and prepare data for analysis.
• Stay up-to-date with the latest advancements in data science and AI.
• Collaborate with engineering and product teams to integrate models into production systems.
• Mentor junior data scientists and contribute to team knowledge sharing.
• Ensure data quality and integrity throughout the analytical process.

• Ph.D. or Master's degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
• Minimum of 7 years of experience in data science, with a focus on predictive modeling.
• Proven expertise in machine learning algorithms (e.g., regression, classification, clustering, time series).
• Proficiency in programming languages such as Python or R.
• Experience with data manipulation and analysis libraries (e.g., Pandas, NumPy, Scikit-learn).
• Familiarity with big data technologies (e.g., Spark, Hadoop) is a plus.
• Strong understanding of statistical concepts and experimental design.
• Excellent communication, presentation, and storytelling skills.
• Ability to work independently in a remote setting and manage projects effectively.

• Assist in data cleaning, transformation, and preprocessing of large datasets.
• Perform exploratory data analysis to identify patterns and insights.
• Help in building and validating statistical and machine learning models.
• Use programming languages such as Python or R for data analysis and modeling.
• Contribute to data visualization and reporting of findings.
• Collaborate with senior data scientists on ongoing projects.
• Learn and apply new data science techniques and tools.
• Document methodologies and results clearly and concisely.

• Currently pursuing or recently completed a Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
• Solid understanding of statistical concepts and machine learning algorithms.
• Proficiency in Python or R, including relevant data science libraries.
• Familiarity with SQL for data extraction.
• Strong analytical and problem-solving skills.
• Excellent communication skills, both written and verbal.
• Eagerness to learn and adapt in a fast-paced environment.
• Previous exposure to data science projects (academic or personal) is a plus.

• Lead the development and deployment of predictive models and machine learning solutions.
• Collaborate with business units to identify opportunities for data science application.
• Perform complex data analysis, feature engineering, and model selection.
• Mentor and guide junior data scientists, fostering technical growth and best practices.
• Communicate insights and recommendations to stakeholders through compelling visualizations and presentations.
• Ensure the scalability, robustness, and interpretability of developed models.
• Contribute to the strategic direction of data science and analytics within the company.
• Stay updated with the latest trends and technologies in data science and artificial intelligence.

• Master's or Ph.D. in Statistics, Computer Science, Mathematics, or a related quantitative field.
• 6+ years of progressive experience in data science and advanced analytics.
• Proven experience in leading data science projects and teams.
• Expertise in statistical modeling, machine learning algorithms, and data mining.
• Strong programming skills in Python or R, and proficiency with relevant libraries.
• Experience with SQL and big data technologies.
• Excellent analytical, problem-solving, and communication skills.
• Experience with cloud-based data science platforms is a plus.

• Assist senior data scientists in collecting, cleaning, and transforming large datasets from various sources.
• Perform exploratory data analysis (EDA) to identify patterns, trends, and insights.
• Support the development and implementation of predictive models using machine learning algorithms.
• Conduct data visualization to communicate findings effectively to stakeholders.
• Help in evaluating model performance and identifying areas for improvement.
• Collaborate with team members on ongoing data science projects.
• Learn and apply statistical techniques and machine learning methodologies.
• Contribute to documentation of data processes and model methodologies.
• Assist in preparing reports and presentations summarizing analytical results.
• Gain exposure to various data science tools and platforms.

• Currently pursuing or recently completed a Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field.
• Basic understanding of statistical concepts and machine learning algorithms.
• Familiarity with programming languages such as Python or R for data analysis.
• Experience with data manipulation libraries (e.g., Pandas, NumPy) is a plus.
• Exposure to data visualization tools (e.g., Matplotlib, Seaborn, Tableau) is desirable.
• Strong analytical and problem-solving skills.
• Excellent attention to detail and ability to work systematically.
• Good written and verbal communication skills.
• Eagerness to learn and contribute in an on-site team environment.
• Must be legally eligible to work in India and available for the duration of the internship.

• Assist in data collection, cleaning, and transformation from diverse sources.
• Perform exploratory data analysis to uncover trends and insights.
• Support the development and implementation of statistical and machine learning models.
• Create data visualizations to communicate findings effectively.
• Contribute to the testing and validation of predictive models.
• Collaborate with senior data scientists and business analysts.
• Learn and apply new data science techniques and tools.
• Document methodologies, findings, and model performance.

• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
• Strong understanding of statistical principles and machine learning algorithms.
• Proficiency in Python or R, including relevant data science libraries (Pandas, NumPy, Scikit-learn).
• Familiarity with SQL for data querying.
• Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau) is a plus.
• Excellent analytical, problem-solving, and critical-thinking skills.
• Good communication and teamwork abilities.
• Eagerness to learn and adapt in a fast-paced environment.

• Design, develop, and implement advanced predictive models using machine learning and statistical techniques.
• Explore and analyze large, complex datasets to identify trends, patterns, and opportunities.
• Collaborate with business stakeholders to understand their needs and translate them into data science problems.
• Develop and deploy scalable data science solutions into production environments.
• Perform rigorous A/B testing and model validation to ensure accuracy and performance.
• Communicate complex analytical findings and recommendations to both technical and non-technical audiences through clear visualizations and presentations.
• Stay current with the latest advancements in data science, machine learning, and artificial intelligence.
• Mentor junior data scientists and contribute to the team's technical growth.
• Work with data engineers to ensure data quality and accessibility for modeling.
• Identify and champion new data sources and analytical methodologies.
• Develop dashboards and reports to track model performance and business impact.
• Contribute to the development of data-driven product features.
• Optimize existing models for improved performance and efficiency.
• Ensure ethical considerations and data privacy are maintained throughout the analytical process.
• Proactively identify areas where data science can provide significant business value.

• Master's degree or Ph.D. in Computer Science, Statistics, Mathematics, Physics, or a related quantitative field.
• Minimum of 5 years of experience in data science, with a strong focus on building and deploying predictive models.
• Proficiency in programming languages such as Python or R, and relevant data science libraries (e.g., scikit-learn, TensorFlow, PyTorch, pandas).
• Solid understanding of statistical modeling, machine learning algorithms (regression, classification, clustering, deep learning), and experimental design.
• Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
• Strong data visualization skills using tools like Tableau, Power BI, or Matplotlib/Seaborn.
• Excellent communication and interpersonal skills, with the ability to explain technical concepts to diverse audiences.
• Demonstrated ability to work collaboratively in a team environment.
• Experience with SQL and database management.
• Ability to work independently and manage project timelines effectively.
• Proven track record of delivering impactful data science solutions.
• Experience with cloud platforms (AWS, Azure, GCP) is advantageous.
• A curious and analytical mindset with a passion for uncovering insights from data.
• Experience in feature engineering and selection.
• Knowledge of MLOps principles is a bonus.