Carrier is the leading global provider of healthy, safe and sustainable building and cold chain solutions with a world-class, diverse workforce with business segments covering HVAC, refrigeration, and fire and security. We make modern life possible by delivering safer, smarter and more sustainable services that make a difference to people and our planet while revolutionizing industry trends. This is why we come to work every day. Join us and we can make a difference together.
About This Role
LenelS2 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 solutions, evaluate & integrate 3rd party solutions, and deploy state-of-the-art data mining and AI-ML models 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 and AI-ML techniques to drive decision making? As an Associate Data Science Engineer, you will be responsible for data collection, cleaning, normalization, feature extraction, supervised and unsupervised learning of customer datasets to deliver analytical systems that improve forensic and real-time security outcomes. These analytical systems you develop in-house and those integrated from 3rd parties will extend the capabilities of our core product ecosystems.
This is hybrid position that can be based in Pittsford, NY, or Salem, OR.
Key Responsibilities
- Participate in extending product capabilities through development and deployment of analytical systems leveraging data mining and AI-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-motivated, but can take directions and deliver results
- Curious problem solver
- Independent drive to learn and expand skillset
Required Qualifications:
- Bachelor’s Degree in an Engineering or Technical Field
- Must be authorized to work in the United States on a permanent basis
Preferred Qualifications:
- Experience in modern advanced analytical tools and programming languages such as R or Python with scikit-learn
- Experience with exploratory data analysis
- Experience with ETL operations sourcing data from SQL, REST APIs, and flat files
- Experience with data visualization technologies, such as Power BI, Tableau, matplotlib, Excel, etc.
- Experience in traditional programming languages such as Java, JavaScript, C++, or C#
- Experience in scripting languages such as PowerShell, Bash, etc.
- Past project or real-world experience applying several 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
- Demonstrated understanding of how to apply machine learning techniques to build AI applications.
- Basic experience with data science platforms, such as AWS SageMaker, SQL, Hive, SparkSQL, etc.
- Comfortable in Windows and Linux environments
- 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
#LI-Hybrid
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