Sr Advanced Software Engr

• *Responsibilities**

• Minimum of 10 years’ experience \- Lead **moderately to highly complex data science and analytics projects** , applying a diverse range of data science, statistical, and machine learning techniques.
• Own the **end\-to\-end development lifecycle** of data science and analytics solutions, including problem analysis, stakeholder engagement, solution design, integration, deployment, maintenance, and support.
• Independently design, develop, test, and maintain **data science models and algorithms** , following disciplined software development and model\-development practices.
• Evaluate emerging analytical and technical capabilities and recommend solutions that **improve productivity and quality, reduce cycle time, and enhance operational reliability** .
• Develop and promote **guidelines, standards, and best practices** for analytics and machine learning models, including model development, validation, deployment, monitoring, and lifecycle management.
• Collaborate with engineering, product, and business stakeholders to translate complex requirements into **scalable, measurable data science solutions** .

• *You Must Have**

• Minimum **2 years of relevant experience** in data science, machine learning, analytics, or related technical disciplines.
• Strong analytical and problem\-solving skills, proficiency with software applications, and the ability to **produce and interpret technical documentation** .
• Working knowledge of **statistics, statistical modeling, and statistical process control** .
• Hands\-on experience with scripting and query languages such as **Python, R, and SQL** .
• Experience developing **analytics dashboards and data visualizations** to communicate insights effectively.
• Practical experience applying **machine learning, neural networks, and deep learning** techniques.
• Ability to translate analytical findings into clear recommendations for both technical and non\-technical stakeholders.

• *Good to Have**

• Experience taking machine learning models from **development through production deployment and monitoring** .
• Familiarity with ML frameworks such as **scikit\-learn, TensorFlow, or PyTorch** .
• Experience with cloud data/ML platforms such as **Azure Machine Learning or Databricks** .
• Understanding of **MLOps** , including experiment tracking, model versioning, monitoring, and reproducibility.
• Exposure to **NLP, Generative AI, LLMs, or RAG\-based applications** .
• Experience working with large or complex datasets and distributed processing technologies such as **Apache Spark** .

Honeywell 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.