Data Scientist II
Job Description
Job Description
Job Description
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 3 rd party analytical components. You will develop new innovative solutions, evaluate & integrate 3 rd 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 those integrated from 3 rd parties will extend the capabilities of our core product ecosystems. RESPONSIBILITIES- Participate in extending product capabilities through development and deployment of analytical systems leveraging data mining, generative AI, and ML techniques.
- Interact with 3 rd 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 3 rd 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
- 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 plus plus or C#
- Comfortable in Windows and Linux environments
- 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
Data Science
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