The advent of new technologies such as enhanced compute power, increased RAM, 4G and 5G and increase in our ability to store and handle large amounts of data effectively has given much required thrust, emphasis and focus on the field of DataScience, Artificial Intelligence and Machine Learning.

In the past decade product development has changed enormously with more effective data driven strategies behind the conception and evolution of meaningful products for the consumers. This is acting as a reason for acquiring skills that will help people contribute effectively in the new realm of technology shift that is currently taking place.I met a lot of people; students and working professionals; aspiring to become technologists, having doubts on which role would be a fit or prove beneficial for them in the long run.

I would ask – what is that the learner wants to be in future which is a more intrinsic question aligned with the inherent strengths of the individual. To help people navigate through this situation, I am listing down the various roles that are in offer with what that role entails in a very simple manner. I hope that this will help people decide what to choose and where they want to build their career.

Data Analyst role – This job profile is all about data including but not limited to data collection, data processing and performing analysis to extract insights for stakeholders and customers. The outcome is often represented in forms of reports, visualizations, trends and patterns.

Key Skills – Proficiency in a database example SQL, Excel, data visualization tools such as Power BI and or Tableau. Data Visualization using Python Libraries such as Matplotlib, Seaborn, Plotly etc. Knowledge of scripting languages such as Python is immensely helpful.

Soft Skills – Storytelling with data, Presentation skills, Communication skills, Problem solving

Machine Learning Engineer – This job profile needs the candidate to be good in programming and problem solving. The incumbent should be able to assess, analyze and organize a large amount of data. The candidate should be able to design, develop machine learning algorithms, deep learning applications and also be able to optimize and test the existing machine learning algorithms.

Key Skills – Good analytical and problem-solving skills, machine learning frameworks such as Keras or PyTorch. Programming language proficiency such as Python or R. There are other roles such as MLOps engineer which are around maintaining and managing the technology stack and the ML pipeline. Those who like to work in operations would find that role interesting.

If you want to pursue your career in DataScience we would invite you to the demo of our existing data science course, to know more https://www.kapilitshub.com/ai-ml-data-science/