Are you curious about careers in data analytics and what options are available after graduation? Hear Eleanor Middlemas, Senior Associate, Climate Risk Modeling at PwC, as she shares her career journey, insights into landing a job in the data world, and examples of how you can position yourself for success. We also discuss the importance of transferable skills and how to transform yourself into a competitive candidate.
Key takeaways
- Entry-level positions involve processing data, lightweight statistical analysis, data organization, creating visualizations, and forming a story around the data.
- Mid-level, senior-level, and lead positions oversee complex machine learning models, have more ownership of projects, and can become people managers.
- Your resume should align with the position you are applying for. Include relevant details and avoid using jargon that the reader may not understand. Following a formula for describing your projects, and putting your education at the bottom of the resume, are also recommended tips.
- When starting out, you can list your academic projects in place of work experience on your resume or LinkedIn. Then, as you gain real-world work experience, you can replace your projects with your professional roles.
The views and opinions expressed in this video are those of the presenter and do not necessarily represent the view of edX or its parent company 2U, Inc.
US
Full Time
