Data Science Engineer

Carrier; New York (NY); On-site; USD 100,000 - 130,000; Full time

Job summary

Carrier is seeking a Data Science Engineer to join their Engineering team in New York, NY. The successful candidate will design and build in-house data solutions, evaluating and integrating 3rd party components to enhance security insights using AI and data mining techniques.

You will play a key role in developing analytical systems that improve forensic and real-time security outcomes while working closely with various teams and ensuring high-quality results.

Qualifications

• Bachelor's Degree or 7+ years of Data Science experience.
• 3+ years of experience in analytical tools like R or Python.
• 3+ years with ETL operations from SQL, REST APIs, etc.

Responsibilities

• Extend product capabilities through analytical systems.
• Evaluate integration feasibility with 3rd parties.
• Design and implement new data-centric solutions.

Skills

Data Science

Data Analysis

Python

R

SQL

Power BI

Education

Bachelor's Degree or 7+ years of Data Science experience

Tools

scikit-learn

Tableau

Excel

Job description

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.