Content Developer Associate at almaBetter
Data Science is making headlines all over the world. This challenging domain is the hot new field that promises to revolutionize almost every industry. From government to healthcare, several industries are already capitalizing on the progress made in Data Science. Moreover, the demand for skilled Data Science professionals is rising every day, and at AlmaBetter, we aim to train and provide industry-ready folks to the world.
Data Science offers a variety of job roles under its umbrella. AlmaBetter’s robust curriculum prepares students to excel and land any data science role efficiently. Let’s have a look at the various job roles in data science.
Data Scientist is the most popular and general role in data science. A Data Scientist’s role includes all the aspects of a project, meaning, dealing with the business side to data collecting and analyzing, and eventually visualizing and presting. In short, a Data Scientist is responsible for understanding the challenges of business and offering solutions using Data processing and data analysis.
Data Scientists are usually also in charge of researching and developing new algorithms and approaches. Often, in MNCs, Data Scientists are team leaders of people with specialized skills. The skillset of a Data Scientist allows them to overlook a project and guide them from start to finish.
Data Analyst is undoubtedly the second most known role in data science. Data Analysts are responsible for various tasks such as visualization, munging, and manipulating a massive amount of data. Occasionally, they have to perform queries on the database, and they are in charge of web analytics tracking and A/B testing analysis.
One of the most effective skills of a data analyst is optimization. They are responsible for creating and modifying algorithms to cull information from massive databases without corrupting the data.
Data Engineers are accountable for building, designing, and strengthening data pipelines. Data Engineers also build and test scalable Big Data ecosystems for companies so that the data scientists can run their algorithms on data systems that are stable and highly optimized.
Moreover, Data Engineers are also responsible for working on batch processing collected data and matching its format to the stored data. In other words, Data Engineers make sure that the data is ready to be processed and analyzed.
Machine learning Engineers
Currently, machine learning engineers are in demand and trending in the Data Science World. However, it is also one of the most challenging roles in Data Science. An Ideal Machine Learning Engineer should be familiar with many machine learning algorithms such as categorizing, clustering and classification. Also, they should be up-to-date with the latest research and advancements in the domain.
Moreover, Machine Learning Engineers are expected to have strong statistical and programming skills and basic knowledge of software engineering.
Data Architects share some shared responsibilities with Data Engineers. Both roles are required to ensure that the data is well-formatted and accessible for data scientists and analysts and improve the performance of the data pipelines.
A Data Architect also constructs the blueprints for data management so that the databases can be smoothly integrated, centralized, and protected with the most suitable security measures.
How AlmaBetter prepares you to land any role in Data Science?
AlmaBetter’s reverse-engineered curriculum such as full stack data science course and masters in data science program covers full-stack data science concepts starting from Python, Analytics Frameworks such as SQL, Excel, tableau, math concepts such as Calculus, Linear Algebra, Probability & statistics to Machine Learning, NLP, Deep Learning, and ML Engineering. The breadth of knowledge and industry-level approach ensured through our rigorous training is enough for you to land a high-paying job in the data science domain.