Working Student (m/w/d) Data Analysis @ Sparrow Networks, GmbH
About Sparrow
Manufacturing and production companies stock spare parts worth $1,000,000,000,000 (yes, $1trn) - 75% of which are rarely or never used. Sparrow changes that - we reduce our customers’ overstock and waste (making them more sustainable).
Sparrow offers a SaaS platform that ensures maintenance teams have the right spare parts when and where they need them, at the lowest possible cost. To do that, we leverage big data, AI algorithms and a network approach.
Our products are used by some of the world’s leading companies.
We’re based in Berlin, serving customers across Europe and growing fast.
About the role
You will be part of the data operations team. The team collects, enriches and classifies data later used by our customers. We use a variety of self-developed and third-party data analysis and processing tools.
As a working student, you will conduct bulk analysis on existing data sets, process new data sets and perform online research.
Your responsibilities will include
Working closely with Data Engineering to improve models
Improve our internal classification system
Analyse customer and supplier data to create and present meaningful insights
Onboard customers to our SaaS product and respond to customer requests
Requirements
You are studying mechanical engineering, information technologies, data science or related subjects
You are proficient in Microsoft Excel, SQL proficiency is a plus (scripting is a double plus)
You are comfortable working with large data sets
You work independently
You like challenges, are ambitious to solve problems and can adapt quickly to new situations
You have good communication skills in English, German knowledge is a plus
What’s in it for you?
Professional development through coaching and mentoring
Diverse tasks with steep learning curves: from scripting through Excel wizardry and up to Machine Learning with new challenges around every corner
Opportunity to define your own field of work and contribute with your ideas
Working with a small and strong team where every voice counts
Your work directly impacts the company’s success
Remote work: we are extremely flexible and open to any working pattern that can adjust to Berlin timezone -/+ 2hrs
How to apply
Send your CV or LinkedIn profile
Respond to the questions in the next step
Weekly working hours: 20 during the semester, 40 during winter and summer holidays