Data Engineering Fellow
This position is hosted under the Constellations Fellowship program. There are a total of 27+ internship positions available for the Spring 2023 semester. To view all positions please visit: https://www.globalwarmingmitigationproject.org/constellations-positions
Data Engineering Fellow
About the Organization:
By leveraging our innovative material traceability technology. Wastezon is currently expanding to electronics reuse, repair and remanufacture markets in addition to the recycling market that we have been operating for the last two years. With Wastezon 2.0, we are so excited to provide additional 3 circular services that catalyze our mission of leveraging technology to create a waste-free world. So far over 500 tons of e-waste have been transacted on the Wastezon app, diverting an equivalent amount of over 3100 tons of carbon emissions.
Internship Description:
To improve our users’ materials traceability experience, we are looking for a Data Scientist Fellow to utilize available data to build relevant models that allow the users to make informed decisions in electronics reuse, repair and remanufacturing.
Responsibilities:
Analyzing massive amounts of data for the discovery of patterns and trends.
Liaising with our material science team to build predictive and comparative models using algorithms and the implementation of ML
Communicating and Storytelling to non-technical staff or stakeholders using immersive data visualization techniques.
Propose solutions and strategies to business challenges.
Collaborate with engineering and product development teams to implement models and monitor outcomes.
Intern Qualifications:
1-2 years of experience in data science or similar roles (internships are also considered)
BSc in Data Science, Computer Science, Mathematics or other relevant education backgrounds (graduate students are preferred)
Experience in statistical modelling, machinelearning, data mining,unstructured dataanalytics, and natural language processing.
Proficiency in statistical and other tools/languages R, S-plus, SAS, STATA, Python.
Familiarity with relational databases and intermediate-level knowledge of SQL.
A naturally inquisitiveand problem-solving mindset.
A passion for data and data science.
Excellent verbal and written communicationskills in English.
Time Commitment: 25 hours / week