At Praelexis we offer internships. Praelexis is a data science consulting company. This means that we complete various projects with clients who each bring their unique problems to us. Basically, if your company collects data, we will be able to help you solve some of your business problems through data science. We work in many industries. In this blog, I will discuss some of the reasons why you should consider applying for an internship at Praelexis.
Praelexis is a consultancy that works in many different fields
Our team comprises specialists with training in many fields each with a passion for data science. As such we can tackle problems in many diverse fields including Finance, Health, Retail, Agriculture and Telematics. Not only does this make for an interesting workplace as every day is different, but completing an internship at Praelexis could help you decide which field you are interested in. Maybe you enjoy the dynamic environment of a consultancy and then you know to look out for that when applying for your future job.
The projects at Praelexis are diverse
Because we work in many different fields, our projects can differ significantly. Another reason why our projects are diverse is that we specialise in every part of the data science life cycle.
The data science life cycle is a process data scientists follow to ensure that they can extract meaningful insights from data. There are many different aspects of the data science life cycle:
- Problem identification: Clearly define the business problem and the objective of the solution.
- Data Acquisition and Collection: Identify and collect the relevant data.
- Data Preparation and Cleaning: This is the preprocess that ensures that the data is in a usable state.
- Exploratory Data Analysis (ETA): This is the visualisation of the data to identify hypotheses for further analysis.
- Feature Engineering: Selecting and crafting features to better the performance of an ML model.
- Model Development and Training: Selecting and fine-tuning predictive of prescriptive models.
- Model Evaluation and Validation: Assess the performance of the model.
- Model Deployment: The model is put into production in a way that it can create value.
- Monitoring and Maintenance: After deployment data scientists check on the model’s performance.
- Feedback Loop and Iteration: The model is refined according to stakeholder feedback.
Anamika Singh has a wonderful blog on the topic of the data science life cycle that you can read here.
At Praelexis, chances are, you will get the opportunity to witness what each of these different aspects of the data science life cycle entails.
At Praelexis we have a learning culture
At Praelexis we value learning and learning from each other. This means that colleagues will be willing to help you when you get stuck or have questions. We have a culture of knowledge sharing and we are willing to walk the extra mile to empower each other.
Praelexis offers Integrative Internships
There are two types of data science internships: Structured Internships and Integrative Internships. With an Integrative Internship, interns are given the opportunity to join an existing team and work on a “real” project. This is real-life exposure that includes witnessing the full cycle of a project: From client interest to solution implementation. You will get the opportunity to witness the data scientist’s day-to-day. At Praelexis we want our interns to integrate into the team, getting the “full Praelexis experience” and receiving as much exposure to the real world of data science as possible.
Conclusion
Ultimately we are a bunch of smart people excited about meeting new people and we’d love to have you! We work in many different fields on various projects, we have a welcoming culture and would love to make you part of our team for the duration of your internship.
*Illustrations: Generated by AI
*Infographics: Aletta Simpson
