Position:
IT Data Scientist
Company:
SLB
Location:
Coimbatore, India
Job Type:
Full Time
Job Mode:
Onsite
Job Requisition ID:
Not Mentioned
Years of Experience:
0 to 3 Years
Company Description
SLB is a globally recognized technology organization dedicated to advancing innovation within the energy sector. For nearly a century, the company has focused on developing technologies that help improve access to energy while supporting sustainability goals across the world.
The organization operates at the intersection of engineering, science, digital transformation, and research, helping industries address complex challenges related to energy production, efficiency, reliability, and environmental responsibility.
With operations spanning numerous countries, SLB provides employees with exposure to international projects, multicultural teams, and opportunities to collaborate with experts from a broad range of disciplines.
The company is investing heavily in digital technologies, artificial intelligence, machine learning, cloud platforms, automation, and advanced analytics to build the next generation of intelligent energy solutions.
SLB promotes a culture where innovation, experimentation, and continuous learning are highly encouraged. Employees are empowered to explore new ideas, challenge conventional thinking, and contribute to technologies that can have a meaningful impact on industries worldwide.
Diversity and inclusion remain central to the company's values. Team members from different backgrounds, cultures, and professional experiences work together to solve real world problems and create practical solutions.
The organization offers structured learning opportunities, career development programs, mentorship, and exposure to cutting edge research initiatives.
Employees have access to a supportive work environment that values creativity, collaboration, technical excellence, and personal growth.
Through a combination of scientific expertise and technological innovation, SLB continues to play an important role in shaping the future of energy and industrial digital transformation.
Profile Overview
SLB is seeking an IT Data Scientist who will contribute to solving challenging business and engineering problems through data driven research, machine learning, optimization, and advanced analytics.
This role is designed for individuals who enjoy working on open ended problems where solutions are not predefined and innovation plays a key role in success.
The selected candidate will work closely with engineers, researchers, product teams, and technology specialists to create intelligent systems capable of improving equipment performance, reliability, and operational efficiency.
A major aspect of this role involves conducting research into emerging technologies and identifying new approaches that can improve diagnostics, predictive maintenance, forecasting, optimization, and decision making.
The position requires strong analytical thinking, mathematical problem solving abilities, and proficiency in programming and machine learning techniques.
Professionals in this role will work with large and complex datasets collected from industrial systems, manufacturing operations, testing environments, and monitoring platforms.
The candidate will be expected to design, develop, validate, and deploy advanced algorithms that help identify anomalies, predict failures, and optimize system performance.
Beyond technical implementation, the role also requires effective communication skills to present findings, research outcomes, recommendations, and technical insights to different stakeholders.
The position provides an opportunity to work on impactful projects involving artificial intelligence, machine learning, deep learning, cloud technologies, optimization techniques, and industrial analytics.
Individuals who are passionate about research, innovation, and applying advanced data science techniques to real world engineering challenges will find this role particularly rewarding.
Key Responsibilities
Research and Innovation
Conduct independent research activities focused on solving complex data related challenges.
Explore new technologies and emerging methodologies relevant to machine learning, optimization, diagnostics, and predictive analytics.
Investigate innovative approaches for improving machinery monitoring and performance analysis.
Evaluate advanced techniques for predictive maintenance and equipment health assessment.
Develop research concepts that can be translated into practical industrial solutions.
Generate original ideas that contribute to technological advancement and business value.
Identify future research opportunities aligned with organizational objectives.
Participate in technical reviews and contribute expertise to research discussions.
Stay informed about developments in artificial intelligence, machine learning, and data science.
Support innovation initiatives by experimenting with new tools, frameworks, and methodologies.
Machine Learning and Advanced Analytics
Design and develop machine learning models for industrial applications.
Apply supervised and unsupervised learning techniques to solve business and engineering challenges.
Utilize deep learning methodologies where appropriate.
Build predictive models that estimate equipment failures and maintenance requirements.
Develop anomaly detection systems for identifying unusual operational behavior.
Create optimization algorithms that improve system efficiency and performance.
Apply statistical modeling techniques to generate actionable insights.
Evaluate and compare multiple modeling approaches to determine the best solution.
Improve model accuracy through feature engineering and data preparation.
Continuously monitor and refine analytical models for better outcomes.
Data Processing and Engineering Support
Work with large scale datasets generated from industrial operations.
Process structured and unstructured data from multiple sources.
Clean, transform, and prepare datasets for analytical use.
Develop automated workflows for data processing activities.
Support data integration initiatives across different systems.
Analyze multivariate datasets containing operational and diagnostic information.
Extract meaningful patterns and trends from complex data environments.
Assist in creating scalable analytical solutions.
Support data quality initiatives to ensure reliable results.
Maintain documentation related to data preparation and analytical processes.
Engineering Collaboration
Collaborate with field engineers to understand operational challenges.
Partner with product teams to identify important monitoring metrics.
Support engineering teams by translating data insights into practical recommendations.
Participate in cross functional project discussions.
Help define analytical requirements for technical projects.
Contribute to the development of intelligent monitoring solutions.
Assist in identifying opportunities for automation and optimization.
Work closely with stakeholders to validate analytical findings.
Provide technical guidance where necessary.
Support the implementation of data driven decision making processes.
Communication and Reporting
Present technical findings clearly to both technical and non technical audiences.
Prepare reports that summarize research outcomes and analytical insights.
Document methodologies, assumptions, and recommendations.
Participate in meetings and technical presentations.
Communicate project progress effectively.
Share knowledge across teams and departments.
Contribute to collaborative problem solving discussions.
Support project planning and execution activities.
Maintain transparency regarding analytical methodologies.
Help stakeholders understand data driven recommendations.
Qualifications
Strong educational foundation in quantitative disciplines such as Computer Science, Statistics, Mathematics, Physics, Data Science, Artificial Intelligence, or related fields.
Ability to understand and solve complex analytical challenges using structured problem solving approaches.
Strong programming capabilities, particularly in Python.
Knowledge of software development best practices and coding standards.
Understanding of linear algebra concepts commonly used in machine learning.
Familiarity with probability theory and statistical analysis techniques.
Knowledge of machine learning algorithms and their practical applications.
Understanding of deep learning architectures and use cases.
Exposure to Generative AI concepts and technologies.
Ability to learn new technologies quickly and independently.
Interest in research oriented problem solving.
Experience working in Unix or Linux environments.
Knowledge of shell scripting for automation tasks.
Basic understanding of cloud computing principles.
Familiarity with application development concepts.
Understanding of data structures and algorithms.
Knowledge of model evaluation and validation techniques.
Ability to interpret analytical results and communicate insights.
Strong attention to detail and commitment to quality.
Good written and verbal communication skills.
Ability to work effectively in collaborative environments.
Required Technical Skills
Programming
Python
Scripting and automation
Software development fundamentals
Code optimization and debugging
Mathematics and Statistics
Linear Algebra
Probability Theory
Statistical Modeling
Data Analysis Techniques
Mathematical Problem Solving
Machine Learning
Regression Algorithms
Classification Algorithms
Clustering Techniques
Deep Learning Models
Predictive Analytics
Generative AI Concepts
Model Evaluation Techniques
Data Science
Data Preparation
Feature Engineering
Exploratory Data Analysis
Predictive Modeling
Data Visualization
Pattern Recognition
Systems and Infrastructure
Unix
Linux
Shell Scripting
Cloud Computing Fundamentals
Application Development Basics
Behavioral Competencies
Strong curiosity and desire to learn.
Creative approach toward solving problems.
Ability to think independently and develop innovative solutions.
Strong collaboration and teamwork mindset.
Effective listening skills.
Professional communication abilities.
Strong presentation skills.
Focus on achieving measurable outcomes.
Commitment to quality and excellence.
Ability to adapt to changing priorities and technologies.
Strong analytical mindset.
Positive attitude toward continuous improvement.
Ability to work in multidisciplinary teams.
Self motivation and accountability.
Professional approach toward problem solving.
Preferred Skills
Experience with TensorFlow.
Experience with PyTorch.
Exposure to computer vision applications.
Understanding of natural language processing.
Familiarity with speech processing technologies.
Knowledge of Google Cloud Platform.
Exposure to Microsoft Azure.
Understanding of cloud based deployments.
Experience designing REST APIs.
Familiarity with backend frameworks such as Django.
Experience with FastAPI.
Knowledge of frontend technologies including JavaScript.
Familiarity with HTML5.
Understanding of Angular based development.
Exposure to full stack application development.
Experience integrating machine learning models into applications.
Benefits and Employee Value Proposition
Opportunity to work with a globally recognized technology organization.
Exposure to cutting edge research and innovation projects.
Access to international career opportunities.
Collaborative and multicultural work environment.
Continuous learning and professional development programs.
Health and insurance related benefits for employees and eligible dependents.
Opportunity to work alongside industry experts and researchers.
Access to advanced technologies and modern development tools.
Inclusive workplace culture that values diversity.
Strong emphasis on employee growth and career progression.
Opportunities to contribute to impactful projects with global relevance.
Exposure to real world industrial applications of artificial intelligence and data science.
Supportive environment for innovation and experimentation.
Opportunity to develop both technical and professional skills.
Long term career growth within a technology driven organization.
Additional Info
This position is ideal for fresh graduates and early career professionals interested in applying data science within industrial and engineering environments.
The role combines research, machine learning, software development, and analytics, providing broad exposure across multiple technical domains.
Candidates will have opportunities to work on real world challenges involving predictive maintenance, anomaly detection, optimization, and intelligent monitoring systems.
The organization values curiosity, creativity, and continuous learning, making it an excellent environment for individuals looking to expand their technical expertise.
Employees can expect to collaborate with experts across engineering, technology, and research disciplines.
Exposure to cloud computing, machine learning operations, software development, and artificial intelligence technologies will help build a strong foundation for long term career growth.
The position offers opportunities to contribute directly to projects that improve operational efficiency and technology innovation.
Individuals with strong analytical thinking, programming abilities, and a passion for solving challenging problems are likely to excel in this role.
The company promotes equal employment opportunities and maintains an inclusive hiring process.
Candidates looking to establish a career in data science, artificial intelligence, machine learning, and industrial analytics should strongly consider this opportunity.
Please click here to apply.
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