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What career can you pursue after our Data Science bootcamp?

Curious to know what our students do after they graduate from our part-time and full-time Data Science bootcamps? Meet our alumni sharing an overview of their diverse job responsibilities and experiences.
Data science is one of the fastest growing and most in-demand careers today. There’s a multitude of jobs on the market requiring you to have data science skills. This article will help you understand the various career pathways our students take after graduating from Data Science bootcamps and scope of their responsibilities.
I am part of the Data Intelligence Unit in the ICT department at JERA, Japan's largest energy producing company that generates over 40% of all electricity in Japan. My team is working on various data driven solutions that directly contribute to the company’s business.

Our flagship project is an AI platform for power plant management such as anomaly detection, equipment failure prediction, etc. We are also working on other AI based services like demand forecasting, equipment inspection using image processing and more.

I am primarily working with RNN and CNN for my current work, along with PostgreSQL, AWS, visualization tools and more.
I joined one of the big four consulting firms in Melbourne, Australia as a technical business analyst within the data and analytics team.

I work as part of an engagement project to deliver business solutions and tech advisory services to clients. The nature of my responsibility shifts according to the expected deliverables of the project I am engaged with, be it data strategy analysis or data visualization utilizing tools such as PowerBI. My role requires a blend of technical, business and creative problem-solving skills. Having had prior work experience in the consumer and retail management industry, Le Wagon has helped me to backfill the technical skills needed to thrive in data consultancy.
I’m a computer vision engineer at Xenera, focused on the application of pose estimation, optical character recognition, and gesture recognition models for use in medical contexts. The majority of my tasks consist of developing a package that can perform some form of CV task — for example, reading prescription sheets for patients or estimating the effective body height of patients with severe spinal curvature — and then transforming that package into an API that can receive requests from the front-end Android application.

Currently I mostly use libraries such as mediapipe, opencv and flask, and deploy most of my applications to Microsoft Azure. As the team is largely Windows/Android based, most communication is done on Teams instead of Slack, and the front-end applications are designed to work mostly on Android hardware.
I joined the R3/Robo team at Arithmer as an AI Engineer. Our team is developing a range of 3D-modeling and robotics solutions for our clients, but my main project at the moment involves fluid simulation for disaster prevention. Because we're a relatively small team, I have the opportunity to contribute to many stages of each project, from AI model development to API deployment. 

So far, I've worked exclusively in Python. I use Docker and Kubeflow Pipelines regularly to deploy scalable pipelines for simulations. These pipelines are built with components that rely heavily on internal libraries.

My responsibilities are more closely aligned with that of a software engineer than that of a pure data scientist, yet the knowledge and skills I developed with Le Wagon are essential to my success in this role. Being part of a cross-functional and diverse team has helped me hone my engineering skills while contributing to meaningful projects.
After graduation, I worked as a data analyst, performing management consulting in a commercial context. I monitored financial target achievement, risks and opportunities, and provided decision-relevant information and recommendations to the management, including an in-depth evaluation of varying scenarios.

I was also developing PowerBI/Excel Dashboards, reports & data models to extract actionable insights from the data. My main tech stack was MS Excel, MS PowerBI, Python and VBA that I used to automate my Excel workflows.

Recently, I moved to the Business Intelligence team and now focused more on the IT infrastructure. I am developing SQL procedures to facilitate data integration and reporting, supporting the implementation of a new planning software, IBM Planning Analytics, to ease the business planning process. The implementation includes the requirements capturing, modeling & design, development, testing, deployment, integration, and documentation.

Interested in our Data Science bootcamps? Check the schedule for our full-time and part-time programs.

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