Lead Data Scientist
Caterpillar Inc.
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Job summary
Caterpillar Inc. is seeking a senior AI/ML leader in Bengaluru to drive data science, AI/ML, and automated solutions across packaging and related enterprise functions.
You will lead cross-functional teams, define analytical scopes, and deliver scalable AI systems powering intelligent automation and business value. The role emphasizes governance, MLOps, and continuous improvement, with strong emphasis on collaboration with global stakeholders and production-ready deployments.
Qualifications
- Bachelor's or Master's in Engineering or CS; data science/AI focus preferred.
- 12+ years overall with at least 2 years in AI/ML or advanced analytics.
- Experience deploying enterprise-scale AI/ML solutions in production.
- Strong communication, stakeholder management, leadership, and collaboration.
- Experience in Packaging, Supply Chain, Logistics, Transportation, or related industrial domains preferred.
- Willingness to support global teams and operations.
Responsibilities
- Lead business requirements, analytical scope, and solution architecture.
- Collaborate with stakeholders and present actionable insights via dashboards and presentations.
- Design, deploy, and optimize AI/ML, deep learning, computer vision, and generative AI solutions.
- Lead large-scale data gathering, feature engineering, and scalable data models.
- Explore AI capabilities using LLMs, NLP, embeddings, and semantic search.
- Establish MLOps, governance, monitoring, retraining for production AI.
- Research emerging AI technologies to improve impact.
Skills
Education
Tools
Job description
When you join Caterpillar, you're joining a global team who cares not just about the work we do – but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here – we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it.
Technology, Digital and Data
When you join Caterpillar, you're joining a global team who cares not just about the work we do – but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here – we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it.
Provides technical leadership in applying Data Science, AI, and Machine Learning to transform large-scale data into actionable insights, intelligent automation, and business value across Packaging and related enterprise functions.
- Lead the definition of business requirements, analytical scope, and solution architecture; translate business needs into scalable technical solutions.
- Collaborate with stakeholders, conduct workshops, and communicate actionable insights through dashboards, visualizations, and executive presentations.
- Lead the design, development, deployment, and optimization of AI/ML, deep learning, computer vision, and generative AI solutions to address complex packaging, supply chain, logistics, and engineering challenges.
- Lead large-scale data gathering, data mining, feature engineering, and data processing activities; create scalable data models and pipelines.
- Explore, promote, and implement AI-driven capabilities using LLMs, agentic AI frameworks, NLP, semantic search, and advanced analytics techniques.
- Drive the development and deployment of predictive, optimization, quality, sustainability, and automation solutions using machine learning and data science methodologies.
- Establish MLOps, model governance, monitoring, retraining, and continuous improvement processes to support reliable production deployment of AI solutions.
- Research and evaluate emerging AI technologies, algorithms, and frameworks to improve solution effectiveness and business impact.
Business Partnership & Requirements Analysis Knowledge of business analysis techniques and stakeholder engagement practices; ability to translate business needs into scalable data science and AI solutions.
- Engages with business leaders, clients, and stakeholders to understand strategic priorities.
- Leads workshops, requirement-gathering sessions, and solution discovery activities.
- Defines analytical scope, success criteria, and technical requirements for AI initiatives.
- Translates complex business challenges into data science, machine learning, and automation solutions.
- Effectively communicates technical concepts to executive, technical, and business audiences.
- Partners with cross-functional teams to drive adoption and business value realization.
Query & Database Access Tools Knowledge of data management systems and data access technologies; ability to retrieve, transform, and optimize enterprise data for analytics and AI applications.
- Writes, optimizes, and supports complex SQL queries across multiple databases and data sources.
- Works extensively with structured and unstructured data environments.
- Designs data retrieval and transformation strategies supporting AI and analytics workloads.
- Consults on query optimization, performance tuning, and database best practices.
- Utilizes big data technologies and distributed data processing frameworks.
- Evaluates database technologies and architectures supporting AI initiatives.
Data Analysis & Statistical Modeling Knowledge of statistical methods, predictive analytics, and data-driven decision-making; ability to transform data into meaningful business insights.
- Performs advanced statistical analysis, predictive modeling, and machine learning experimentation.
- Uses statistical techniques to identify patterns, trends, anomalies, and business opportunities.
- Translates complex analytical findings into actionable business recommendations.
- Develops metrics, KPIs, and analytical frameworks to support strategic decisions.
- Evaluates model accuracy, effectiveness, and business impact using statistical methodologies.
- Communicates analytical insights to both technical and non-technical stakeholders.
Artificial Intelligence & Machine Learning Knowledge of machine learning, deep learning, generative AI, computer vision, and agentic frameworks; ability to develop, deploy, and manage AI-based solutions that drive business outcomes.
- Leads the deployment of machine learning, deep learning, computer vision, and generative AI solutions.
- Develops and implements LLM-based applications using agentic AI, NLP, embeddings, summarization, and semantic search technologies.
- Selects, trains, evaluates, and optimizes models using TensorFlow, PyTorch, Scikit-Learn, PySpark MLlib, and related frameworks.
- Monitors model performance and implements retraining, scalability, and error-handling strategies.
- Coaches and mentors teams on AI technologies, methodologies, and best practices.
- Applies AI solutions to solve complex packaging, logistics, engineering, and supply chain business challenges.
Programming Languages & Software Development Knowledge of programming concepts, software development practices, and application development frameworks; ability to build scalable AI-enabled applications and enterprise solutions.
- Demonstrates expertise in Python and SQL.
- Develops scalable AI applications using Streamlit, Gradio, and cloud-native architectures.
- Integrates AI services with enterprise business systems and backend platforms.
- Guides teams in selecting development tools, frameworks, and coding standards.
- Oversees development activities to ensure quality, maintainability, and performance.
Cloud & Data Engineering Knowledge of cloud platforms, data engineering practices, and enterprise-scale distributed systems; ability to design and implement scalable AI and analytics solutions.
- Works with relational and non-relational databases, data warehouses, big data platforms, and caching technologies.
- Utilizes cloud-native architectures to support AI, analytics, and automation solutions.
- Evaluates emerging cloud technologies and recommends improvements.
MLOps & Production Deployment Knowledge of model lifecycle management, MLOps frameworks, and deployment architectures; ability to operationalize AI solutions at enterprise scale.
- Builds automated deployment, monitoring, governance, and model management solutions.
- Ensures the scalability, reliability, security, and maintainability of production AI systems.
- Develops monitoring strategies to track model drift, performance degradation, and operational issues.
- Drives continuous improvement of AI operations and deployment methodologies.
Domain Expertise – Packaging, Supply Chain & Logistics Knowledge of packaging engineering, supply chain, logistics, transportation, procurement, or manufacturing operations; ability to apply AI/ML technologies to business challenges in these areas.
- Applies AI/ML techniques across relevant enterprise domains.
- Understands operational workflows, business processes, and optimization opportunities within industrial environments.
- Develops AI-driven solutions for quality prediction, defect detection, optimization modeling, sustainability, and automation.
- Leverages domain expertise to accelerate solution adoption and business impact.
- Collaborates with engineering and business teams to identify high-value AI opportunities.
- Provides technical leadership on AI initiatives supporting Packaging and Supply Chain transformation.
- Bachelor's or Master's degree in Engineering or Computer Science; Data Science, Artificial Intelligence, Statistics, or a related field preferred.
- 12+ years of professional experience, including at least 2 years in Data Science, Machine Learning, Artificial Intelligence, or Advanced Analytics.
- Demonstrated experience deploying enterprise-scale AI/ML solutions in production environments.
- Strong communication, stakeholder management, leadership, and collaboration abilities.
- Experience in Packaging, Supply Chain, Logistics, Transportation, Procurement, or related industrial domains preferred.
- Willingness to support global teams and business operations as needed.
Caterpillar is not currently hiring individuals for this position who now or in the future require sponsorship for employment visa status. However, as a global company, Caterpillar offers many job opportunities outside India, which can be found through our employment website at www.caterpillar.com/careers.
Our goal at Caterpillar is for you to have a rewarding career. Our teams are critical to the success of our customers, who build a better world. Here, you earn more than just a wage. Because we value your performance, we offer a total rewards package that provides day-one benefits along with the potential for a variable bonus. Additional benefits include paid annual leave, flexi leave, medical coverage, and insurance, prorated based on hire date.
Caterpillar Inc. is the world's leading manufacturer of construction and mining equipment, off-highway diesel and natural gas engines, industrial gas turbines, and diesel-electric locomotives. For nearly 100 years, we've helped customers build a better, more sustainable world and have remained committed to contributing to a reduced-carbon future. Our innovative products and services, backed by our global dealer network, provide exceptional value that helps customers succeed.
This position requires working onsite five days a week.
Visa Sponsorship is not available for this position.
September 24, 2026 - October 1, 2026
Caterpillar is an Equal Opportunity Employer. Qualified applicants of any age are encouraged to apply
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