Big data is revolutionizing businesses in all categories. Organizations who are able to successfully able to leverage data and learn from it are those succeeding to the highest standard in the current marketplace.
After graduating a big data course, you’ll likely be greeted by several companies searching for their next big data scientist to come in and help them get an edge over the competition. As a graduate, several things may be expected of you in the hiring process. If you’re determined to find suitable employment as a data scientist, here are a few things to remember going forward.
1. Tip 1 – Showing them the basics of what you can build.
As a data scientist, be prepared to show them how you can procure and analyze data. Be able to explain how this can help or change how they do business. The first data product you build should be something straightforward, simple, and highly effectively. Predicting outcomes is something that can take years to effectively build. Early on, focus on less challenging data projects such as a platform to monitor key KPIs, business health, or something management-related.
2. Tip 2 – You will be expected to review their data.
Walking into a job in big data, you never know what kind of data you might be expected to review. It could be anything from simple text to audio, images, or video. If it’s a company with medical records or financial records, that’s a whole different ballgame as well. You may need to procure a security clearance. There may also be specific standards to adhere to in storing or retrieving data. In a big data job, ideally, you’ll want to come in knowing what your review strategy will be.
3. Tip 3 – Aggregating and building a data pipeline.
A lot of companies don’t make the most from their data and they don’t aggregate it correctly. There’s some that could be non-digital, other pieces under security lock. You may also have corrupted data to process or new, unprocessed data to handle. You will need the skill to collect data from multiple sources and create a data pipeline through which different products can be built. Throughout the data pipeline building process, security is also going to have to be prioritized.
4. Tip 4 – Go for jobs where you specialize and have interest.
No big data scientist is an expert in all things data. You’ll want to zero in on employment opportunities that meet your interest and skillset. From data visualization to data preparation, artificial intelligence, and all types of data science, don’t go into a job without the knowledge that your skillset and software experience meet the qualifications. Be honest about where your gaps are, when/if you are asked.
5. Tip 5 – Ready a portfolio of past work for an employer to see.
Have a portfolio of what you’ve built prior ready to view. Be ready to discuss what you contributed to each project. Many employers will hire, in part, based off the data talent you display in your portfolio. As data science is an emerging field and the hiring manager may not necessarily have full knowledge of the value of certain projects, being able to sell your experiences as transferable to where you’re applying is also a great skill to have as a big data graduate.
6. Tip 6 – Be more than your academics.
Although big data is an emerging field and there’s a lot of job opportunities here, there’s still competition for the roles you’ll be applying for. Be ready to showcase yourself beyond the academics. Remember, you’re not being hired to achieve what you’ve already achieved. As accomplished a big data scientist may be, their value is based on how they can support a business’ objectives in the present and future.
