Data Scientist II

Honeywell
Bangalore, UK
12 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Compensation
£37,316.0
Working hours
Regular working hours

Tech stack

Artificial Neural Networks Microsoft Azure Big Data Business Software Decision Tree Learning Cluster Analysis Databases Data Files Data Visualization Digital Data Statistical Hypothesis Testing Python (Programming Language)
+7 more
Machine Learning SQL Databases Web Platforms Web Services Data Processing Data Analytics Programming Languages

Job description

Honeywell is transforming from a traditional industrial company to a contemporary digital industrial and software business. Our goal is not only to produce great products but to deliver the seamless and effortless digital experience our customers expect. We are looking for someone passionate about data and delivering actionable insights to help the company progress on our digital journey. The Data Scientist will be responsible for creating, updating, and deploying complex data sets to understand customer behavior, improve the customer experience, and drive adoption of Honeywell’s new digital platforms. The Data Scientist will also analyze both digital and non-digital data to provide actionable insights and present data-based recommendations and opportunities for driving new growth and efficiencies., * Performing statistical analysis to identify trends, patterns, and correlations.

  • Collecting, cleaning, and preprocessing large and complex datasets
  • Developing and maintaining datasets, models & databases
  • Develop data visualizations and self-service tools.
  • Manage data and analytics projects, delivering results in a timely manner.
  • Collaborating with cross-functional teams to develop data-driven solutions.

Requirements

  • Bachelor’s Degree with a minimum 5 years of experience in manipulating data sets and building statistical models.
  • Strong problem-solving skills with an emphasis on product development.
  • In-depth understanding of SQL.
  • Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets.
  • Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
  • Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.

WE VALUE

  • Strong analytics skills: ability to assess data, drive insights, and make recommendations.
  • Exposure to Azure web services
  • Excellent verbal and written communication and presentation skills

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