Über
Honeywell is looking for a data driven professional to join its Data Science engineering team to design & build in-house as well as evaluate and integrate 3rd party analytical components. You will develop new innovative solutions, evaluate & integrate 3rd party solutions, and deploy state-of-the-art AI-ML models and data mining techniques that leverage physical access control system datasets to unlock new security insights for end-user customers. Do you enjoy integrating systems together, mashing-up datasets and analyzing them by leveraging state-of-the-art data mining, generative AI, and ML techniques to drive decision making? As an Advanced Data Scientist, you will be responsible for data engineering, leveraging closed and open-source LLMs, text and multi-modal embedding models, and development of new generative AI systems and ML models to deliver analytical systems that improve forensic and real-time security outcomes. These analytical systems you develop in-house and You will report directly to our Director of Engineering, and you'll work out of our Pittsford, NY location on a Hybrid work schedule. As a Data Scientist II here at Honeywell, you will be responsible for developing and implementing advanced data analytics models and algorithms to solve complex business problems. You will work closely with cross-functional teams to understand business needs and translate them into data-driven solutions. Your role will involve leveraging machine learning, statistical modeling, and data analysis techniques to provide actionable insights that drive business value. In this role, you will impact the business by optimizing processes, reducing costs, and identifying growth opportunities through data-driven insights. Your contributions will help position Honeywell at the forefront of data-driven innovation, leveraging cutting-edge technologies and advanced analytics to propel the business forward. Responsibilities
KEY RESPONSIBILITIES Participate in extending product capabilities through development and deployment of analytical systems leveraging data mining, generative AI, and ML techniques. Interact with 3rd parties to evaluate integration feasibility and licensing of technologies and analytic components Design, prototyping, and implementation of new data-centric solutions Effectively communicate and collaborate with local teams, international teams, and 3rd parties Contribute to build versus buy decisions Work closely with members of Product Management, New Product Development, Quality Assurance, and end users as may be necessary to bring solutions to life Self-starter that can take minimal direction and deliver results Curious problem solver Qualifications
YOU MUST HAVE BS or MS in an appropriate technology field (Computer Science, Statistics, Applied Math, etc.) 2+ years of experience in modern advanced analytical tools and programming languages, including Python with scikit-learn Some experience with exploratory data analysis Some experience with ETL operations sourcing data from SQL, REST APIs, and flat files Basic experience with data visualization technologies, such as Power BI, Tableau, matplotlib, Excel, etc. 2+ years of experience in traditional programming languages such as Python, JavaScript, TypeScript, C++, or C# Comfortable in Windows and Linux environments WE VALUE Some exposure to building generative AI applications leveraging embeddings, LLMs, VLMs, vector databases, data source APIs, and agentic patterns/frameworks Basic understanding of various deployment topologies including on-premises, hybrid, and cloud for production generative AI applications Basic understanding of building predictive and decision-making AI applications. Some exposure to using cloud services from AWS, Azure, or GCP to develop solutions. Awareness of computer vision and image/video analysis, including object detection, recognition, tracking, and identification Some exposure with application of data mining algorithms and statistical modeling techniques such as clustering, classification, regression, decision trees, neural networks, SVMs, anomaly detection, recommender systems, pattern discovery, and text mining Problem Solving: Ability to solve problems using analytical thinking, reconciling viewpoints, and evaluating technologies. Communication: Demonstrates effective verbal and written communication skills when explaining complex technical issues to both technical and non-technical audiences Continuous learning mindset
Sprachkenntnisse
- English
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