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Open nowPosted 973 days ago

Data Science Engineer

Carrier4,192 open roles

Where
New York, United States
Work mode
On site
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Your applicationOpen nowData Science EngineerCarrier · New York, United States

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The clock on this job

Early applications get read.

11.8% of postings close within 7 days. Measured by our own scanner across the market. Carrier postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.8%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: posted 973 days ago

Carrier median: 1 days open

The posting

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 a 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.

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-starter that can take moderate direction and deliver results
  • Curious problem solver

Required Qualifications:

  • Bachelor’s Degree OR 7+ years of Data Science professional experience & High School Diploma/GED
  • 3+ years of experience in modern advanced analytical tools and programming languages such as R or Python with scikit-learn
  • 3+ years of experience with exploratory data analysis
  • 3+ years of experience ETL operations sourcing data from SQL, REST APIs, and flat files
  • 3+ years of experience with data visualization technologies, such as Power BI, Tableau, matplotlib, Excel, etc.
  • 3+ years of experience in traditional programming languages such as Java, JavaScript, C++, or C#
  • 3+ years of experience in scripting languages such as PowerShell, Bash, etc.

Preferred Qualifications:

  • Experience with many 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
  • Experience applying machine learning techniques to build AI applications.
  • Experience with data science at scale using AWS SageMaker, SQL, Hive, SparkSQL, etc.
  • Comfortable in Windows and Linux environments
  • Experience integrating 3rd party analytic components into commercial products
  • 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

RSRCAR

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