Data Science is the latest in line of emerging new software based industries that promises a high-paying job and a continuous professional growth. If you have already chosen a career path in the field, then you would have realised the huge potential in the sector. Almost all MNCs across the world are adapting data management systems into their management teams, and small companies are following suit. This means there are plenty of job opportunities in the field for eager professionals like you who have completed a data science course.
Positions like Data Scientist, Data Architect, Data Science Manager, Data Scientist, Data Analyst, Data Warehouse Engineer, Business Intelligence Developer, Computer Vision Engineer, etc. are all opening up across companies, and are waiting to be filled by experienced professionals. However, the competition for the job is also high. Therefore, it is up to you to differentiate yourself from the crowd and project yourself as the ideal candidate. You can do this by creating an impeccable portfolio and improving it regularly. When you create your portfolio you should consider many things the industry, relevance, scope of the project, skills used and showcased, and a number of other things. In this we article, we show you how to build a strong portfolio in data science before applying for an interview.
Choose Projects from Different Industries
The first step is to diversify your data management experience. You can do this by choosing projects spanning multiple sectors and industries. From retail industry, to manufacturing, to service sectors, there are plenty of industries that rely on data science for their progress. As a data science engineer, you can encash this opportunity and work on different projects. This will add up to your experience and will reflect on your portfolio in the long run.
Explain Problem Clearly in Each Domain
The next thing you can do is to identify data patterns, and errors within data sets, implementation, testing, and other processes in every domain. For example, if you are able to gain significant insights from unstructured data, you can assist an organisation in better decision making. This makes you excel in data analytics. Or, if you can identify and rectify errors in data systems, and design, your skill as a data scientist will naturally improve. Whichever domain you are currently in, be it design, systems, analytics, or value, you must be willing to venture into other domains and learn about them. This experience based knowledge of the domains will give you a cutting-edge advantage in your career progression.
Include Information about Data Cleaning & Pre-processing
These are basic skills in data science, and being good at them means you can progress faster in the corporate ladder. Your ability to transform raw datasets into an understandable format, and modify them to correct erroneous data, or remove redundancies in them, or deal with missing/incomplete data will help you process data sets fast. These are essential skillsets for data scientists and analysts. By showcasing your expertise in this, you establish your personal brand among your fellow data science professionals and Give written samples for your experience in these skills and it adds more points to your portfolio.
Give Briefs about all the Tools Used
You will be using multiple tools such as Java, Python, MATLAB, SQL, Spark, etc. You can also be an expert in one or many of these tools. While working on your portfolio, make sure you brief about your expertise in all the tools you know off. You can also improve your portfolio by learning new languages and tools and adding it to your resume. Recruiters look for professionals who have knowledge in multiple tools. Knowing multiple languages is an advantage for you, for you can make easy progress through the data management hierarchy. If you seek to learn more tools, you can always join a course on data science. The data science course fees are nominal in many institutes, and you can learn selective skills that can help in your career progression.
Provide Data Visualisation
Your skill in Microsoft Excel and other visualisation tools can be put to better use in your portfolio by providing visualisation of your expertise in data science field. In the field you will be using charts, graphs, and maps to understand outliers, trends, and patterns in data. Use the same to showcase your skillset in your portfolio. Your ability to visualise your data will impress recruiters who seek that valuable skill in professionals. It shows how well you communicate about yourself and in general.
Share Your Works on LinkedIn / Social Media
LinkedIn is the professional networking social media and is used by HR managers around the world. So, it is the easiest way for you to get in front of the people who are looking for experts in the field of data science. Build your personal brand on LinkedIn by sharing your project updates, case studies and by helping your fellow data scientists. This way you add credibility and authority to your position as an expert in the field. You can take showcase your experience in LinkedIn, and other social/professional platforms to attract potential employers to you. The more skillsets you have and the more visibility you gain, the more offers you will gain.
If you are new to data science and you wish to start a career in the field, you can always join a data science academy and complete a certified course. At Indras Academy, we have some of the best data science courses in Bangalore. A course typically takes about 6 months to complete, but by the end of the courses, you will have gathered all the knowledge, technical skills, and a good portfolio that gets you your dream job.
