Senior Data Scientist

2 weeks ago

hyderabad, India CES Full time
Senior Data Scientist - Industrial Applications
Job Summary:
The Senior Data Scientist for Industrial Applications is responsible for leveraging data analytics and machine learning techniques to optimize industrial processes, enhance efficiency, and drive innovation within the organization. This role requires a good understanding of optimization and forecasting methodologies for industrial applications (manufacturing, energy, transportation, logistics or any other industrial) coupled with strong analytical skills and proficiency in programming languages and data manipulation tools.
Key Responsibilities: Work closely with subject matter experts and stakeholders to understand business objectives and translate them into analytical solutions - to contextualize data insights and develop actionable recommendations.
Data Analysis and Modeling:
• Perform exploratory data analysis (EDA) to understand underlying patterns and trends in industrial data.
• Develop predictive and prescriptive models using machine learning algorithms to forecast equipment failures, optimize production processes, and improve overall operational efficiency.
• Implement statistical methodologies for analysing process variability and identifying opportunities for improvement.
Data Integration and Management:
• Extract, transform, and load (ETL) data from disparate sources, including sensors, IoT devices, databases, and external APIs.
• Develop data pipelines and workflows for efficient data ingestion, cleansing, and preparation.
• Ensure data quality and integrity throughout the data lifecycle, implementing measures for data validation and anomaly detection.
Model Deployment and Monitoring:
• Deploy machine learning models into production environments, integrating them with existing systems and processes.
• Establish mechanisms for monitoring model performance, tracking key metrics, and conducting regular model retraining as needed.
• Collaborate with IT teams to ensure scalability, reliability, and security of deployed solutions.
Cross-functional Collaboration:
• Work closely with cross-functional teams, including engineering, operations, and IT, to drive data-driven decision-making and foster a culture of innovation.
• Communicate complex technical concepts and findings to non-technical stakeholders in a clear and concise manner. Stay abreast of industry trends, emerging technologies, and best practices relevant to industrial applications of data science. Provide mentorship and guidance to junior members of the data science team, fostering their professional growth and development
Qualifications : • Master's or Ph.D. in a quantitative field such as Data Science, Computer Science, Engineering, Statistics, or Operations Research.
5+ years of experience in data science or related roles, with a focus on industrial applications.
• Proficiency in programming languages such as Python, R, or Scala, along with experience with data manipulation and analysis libraries (e.g., pandas, NumPy, scikit-learn).
• Strong understanding of machine learning algorithms and techniques, including supervised and unsupervised learning, time series analysis, and deep learning.
• Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau) and SQL databases.
• Familiarity with big data technologies such as Hadoop, Spark, or Kafka is a plus.
• Excellent problem-solving skills, critical thinking abilities, and attention to detail.
• Strong communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams.
• Proven track record of delivering impactful data science solutions in an industrial setting
Interested candidates can please share your resume at

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