Data Scientist

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

Innovate to solve the world's most important challenges

Join a company that is transforming from a traditional industrial company to a contemporary digital industrial business, harnessing the power of cloud, big data, analytics, Internet of Things, and design thinking. You will lead change that brings value to our customers, partners, and shareholders through the creation of innovative software and data-driven products and services. You will work with customers to identify their high value business questions and work through their data to search for answers. You will be responsible for working within Honeywell to identify opportunities for new growth and efficiency based on data analysis.

Key Responsibilities

Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.

• Mine and analyze data from company databases to drive optimization and improvement of data quality.
• Selecting features, building and optimizing classifiers using machine learning techniques.
• Anomaly detection to improve Data Quality.
• Data mining using state-of-the-art methods.
• Enhancing data quality using AI/ML based approaches.
• Processing, cleansing, and verifying the integrity of large volume of data used for analysis
• Doing ad-hoc analysis and presenting results in a clear manner

Rapid Proto-type development

YOU MUST HAVE

• We're looking for someone with 5 years of experience manipulating data sets and building statistical models, has a bachelor's or Master's in Statistics, Mathematics, Computer Science or another quantitative field, and is familiar with the following software/tools:
• Experience querying databases and using statistical computer languages: Python, R, SLQ, etc.
• Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Random Forest, Decision Trees, etc.
• Experience working in processing texts using NLP methods and Image Processing.
• Great communication skills.
• Good applied statistics skills, such as distributions, statistical testing, regression, etc.
• Good scripting and programming skills.