Sr Advanced Data Scientist

Posted 11 Days Ago
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Bengaluru, Bengaluru Urban, Karnataka, IND
In-Office
Senior level
Aerospace
The Role
Leads research, design, development, and deployment of AI-powered solutions using Generative AI, LLMs, machine learning, and deep learning. Builds data pipelines, prepares structured and unstructured data, develops production-grade models, and establishes AI/ML governance and lifecycle practices. Collaborates cross-functionally to deliver scalable analytics products, conducts proofs of concept, and applies modern software engineering, testing, CI/CD, and MLOps practices.
Summary Generated by Built In

We are seeking an experienced Advanced Data Scientist to join our AI and Analytics product development team. In this role, you will drive the research, design, development, and deployment of advanced AI-powered solutions leveraging Generative AI, Machine Learning, Deep Learning, and modern Data Engineering technologies. You will work on high-value, complex business challenges, transforming large-scale industrial and enterprise data into actionable insights and intelligent products.

The ideal candidate combines strong expertise in AI/ML model development with robust software engineering and data engineering capabilities, enabling the delivery of scalable, production-grade solutions from concept through deployment.

Responsibilities

Key Responsibilities

  • Research and apply advancements in Artificial Intelligence, including:
    • Generative AI and Large Language Models (LLMs)
    • Causal AI
    • Knowledge Graphs
    • Machine Learning and Deep Learning
  • Design, develop, and deploy scalable AI/ML solutions that solve complex customer and business problems.
  • Lead research initiatives, proof-of-concepts, pilot programs, and rapid prototyping activities to evaluate emerging technologies and product opportunities.
  • Build and optimize data pipelines, data engineering workflows, and analytics platforms to support machine learning applications.
  • Process, transform, and prepare structured and unstructured data for advanced analytics and AI model consumption.
  • Collaborate with product managers, domain experts, software engineers, architects, and stakeholders to deliver end-to-end solutions.
  • Perform problem analysis, solution design, development, integration, testing, deployment, maintenance, and support of analytics and AI products.
  • Establish best practices, standards, and governance processes for AI/ML model development, deployment, monitoring, and lifecycle management.
  • Develop high-quality, maintainable, and testable software using modern engineering practices including automated unit testing and CI/CD.
  • Evaluate and adopt productivity-enhancing tools, frameworks, and emerging technologies to accelerate innovation and delivery.
Qualifications

Required Qualifications

  • Bachelor's or master’s degree in Engineering,  Applied Mathematics, Statistics, or a related discipline.
  • 8 to 14 years of overall experience with at least 4 years of relevant experience in AI/ML, Analytics, Data Science, or Data Engineering product development.
  • Strong analytical and problem-solving skills with the ability to derive insights from complex data.
  • Experience developing and deploying machine learning or AI-based products in production environments.
  • Experience working in agile product development organizations.

Technical Skills

Artificial Intelligence & Machine Learning

  • Generative AI
  • Large Language Models (LLMs)
  • Machine Learning
  • Deep Learning
  • Statistical Modeling
  • Predictive Analytics
  • Knowledge Graphs
  • Causal AI
  • Model Deployment and Monitoring

Programming

  • Advanced Python
  • PySpark

Data Engineering

  • Data Processing and Transformation
  • Data Pipeline Development
  • Data Preparation for ML Workloads
  • Python Packaging and Deployment

Software Engineering Practices

  • Automated Unit Testing (PyTest)
  • CI/CD and DevOps Practices
  • Git / Bitbucket
  • GitHub Copilot
  • Scalable and Performant Application Design

Preferred Qualifications

  • Experience working with Industrial Automation, Manufacturing, Process Control, or Industrial IoT data.
  • Experience supporting fast-paced product engineering and innovation teams.
  • Exposure to MLOps, AI platform development, and large-scale distributed data processing.
  • Strong communication, stakeholder management, and cross-functional collaboration skills.
  • Demonstrated ability to learn, explore, and adopt emerging technologies aligned with organizational objectives.
About UsHoneywell Technologies is a global, pure-play automation company with a legacy of innovating to help solve the world’s most mission-critical challenges, enhancing the quality of life for people and communities around the world. We serve the building, industrial and process sectors with a broad portfolio of services, solutions and products, underpinned by our Honeywell Technologies Accelerator operating system and Honeywell Technologies Forge intelligence layer. By combining the deep domain expertise of our more than 50,000 employees with decades of data from our global installed base, we are uniquely positioned to lead the industrial sector’s transition from automation to autonomy.

Skills Required

  • Bachelor's or master's degree in Engineering, Applied Mathematics, Statistics, or a related discipline
  • 8 to 14 years of overall experience
  • At least 4 years of relevant experience in AI/ML, Analytics, Data Science, or Data Engineering product development
  • Strong analytical and problem-solving skills
  • Experience developing and deploying machine learning or AI-based products in production environments
  • Experience working in agile product development organizations
  • Experience with Generative AI and Large Language Models
  • Experience with machine learning, deep learning, statistical modeling, predictive analytics, knowledge graphs, and causal AI
  • Advanced Python and PySpark
  • Experience with data processing, transformation, pipeline development, and data preparation for machine learning workloads
  • Experience with automated unit testing, CI/CD, DevOps practices, Git, or Bitbucket
  • Experience with Industrial Automation, Manufacturing, Process Control, or Industrial IoT data
  • Experience supporting product engineering and innovation teams
  • Exposure to MLOps, AI platform development, and large-scale distributed data processing
  • Strong communication, stakeholder management, and cross-functional collaboration skills
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The Company
Mississauga, Ontario
10,000 Employees
Year Founded: 1914

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