Data Scientist

At TE, you will unleash your potential working with people from diverse backgrounds and industries to create a safer, sustainable and more connected world. 

Job Overview

TE offers an exciting opportunity to solve key business challenges through leading-edge data analytics. As our new Data Scientist, you will help specify, design, and develop applications that connect our business partners to our solutions that ease decision-making. You will support our advanced analytics projects by:   1) Collaborating with business partners to discuss business challenges, define requirements, and design analytics solutions 2) Implementing analytics applications in Python with a focus on user experience and scalability and 3) Performing usability testing. We will form a unique and dynamic department working with innovative technologies in a modern and visionary organization. As a data scientist, you know how to interpret data in a smart way and develop solutions that bring value to the customer, you enjoy diving into data, and you know how to present findings to serve customer needs.   RESPONSIBILITIES:

• Collecting and analyzing large sets of data from various sources, cleaning and transforming it, and then analyzing it to identify trends, patterns, and insights.
• Use statistical and machine learning techniques to build predictive models that can be used to forecast future outcomes or make informed decisions.
• Communicate findings to stakeholders in a clear and concise manner. This may involve creating reports, visualizations, or presentations.
• Work closely with other teams within the organization, such as marketing, product development, or operations, to identify opportunities to leverage data and improve business outcomes.
• Stay up to date with industry trends in data science, machine learning, and artificial intelligence to ensure they are using the most effective techniques and tools.
• Ensure that the data they work with is secure and private, adhering to legal and ethical guidelines regarding the collection and use of data.

What your background should look like:

• Bachelor’s degree (engineering, computer science or equivalent), Masters and/or doctorate is a plus
• Proficient in analyzing large and complex datasets.
• Must have experience with machine learning techniques such as regression, classification, clustering, and natural language processing
• Proficient in programming languages such as Python, R, and SQL. Knowledge of big data technologies such as Hadoop and Spark can be useful.
• Excellent communication skills
• Must be curious and creative in exploring data and discovering insights that may not be immediately obvious
• Should be able to think critically and evaluate the validity of data and models

Competencies

Values: Integrity, Accountability, Inclusion, Innovation, Teamwork