Data scientists should possess these top 10 data science skills to land their dream job
Data science has become an important part of technology development and is among the most popular domains for emerging tech professionals. Based on reports, data science dominates the tech job ranking with over 37% hiring growth in the past couple of years. The integration of data science technologies is revolutionizing almost every industry and its popularity is gaining momentum by the day. The growing hiring craze has led emerging tech professionals to realize the significance of garnering such skills, hence, they are now upskilling and re-learning some of the most important data science skills. The top data science skills will enable aspiring techies to pursue a career in data science and its adjoining domains. Data science has a huge scope in the future and chasing a career in this domain would help them succeed in their careers and aid in better decision-making for their respective companies. Here, we have listed the top 10 data science skills that tech aspirants should learn to get their dream job in the next hiring season.
Learning Mathematical Concepts like Statistics and Probability
To create high-quality models, aspiring data scientists should possess a deep understanding of mathematical concepts like statistics and probability. These concepts directly relate to machine learning, which continues to evolve at every growing stage. Professionals claim that it is necessary to understand these concepts since machine learning and algorithm formation are huge parts of data science jobs.
Understanding Programming Languages
To advance the careers of data science professionals, they have to understand and learn programming languages. They have to be proficient in advanced statistical modeling tools and have a deep understanding and knowledge of programming, along with forming a strong foundation in mathematics and statistics. A variety of programming languages like Python, JavaScript, and R are extensively used in forming efficient data science pipelines.
Proficient in Handling Unstructured and Large Datasets
Proficient data scientists should have enough experience with handling unstructured and large datasets that come from different channels and sources. The core responsibility of a data scientist is to prepare the data for effective analysis, and with the growing amounts of data, aspiring data scientists should learn how to practically handle huge amounts of datasets and prepare them for extracting meaningful insights.
Ability to Use Automated Analytics Tools
This is one of the top data science skills that aspiring techies should ace. Automated analytics tools enable professionals to extract the results of their data science processes and explore the data; besides, the tools also attempt to share these results with less-technical people, so that they understand them clearly.
Good at Data Visualization
Nowadays, data visualization has emerged as one of the most significant aspects of data analysis. It is now critical to convey information in a way that is both understandable and pleasant to the eye. Efficient data scientists know how to connect data with the end-users efficiently, and it is mostly performed through data visualization.
Learn Software Engineering Principles
A thorough understanding of software engineering principles is a must for data scientists. They should learn how to build high-quality code that will not cause problems during production. Besides, software engineering topics also massively entail information about the basic lifecycle of software development projects, data types, compilers, and others. Aspirants do not have to possess a degree in software engineering, but learning these fundamentals would surely help.
Data Wrangling
Data wrangling can help data professionals to remove corrupted data and arrange it accordingly. The ability to process and use it for various analytical purposes is one of the most important skills that data science experts should possess.
AI and Machine Learning Skills
Machine learning and artificial intelligence will surely not take away your job, but they definitely will make your job easier. AI and machine learning are extensively used in businesses and help data scientists to work better and faster. However, their biggest challenge would be to understand the right data before training an AI model to perform human tasks.
Strong Business Acumen
Besides possessing technical capabilities, aspiring data scientists should also possess strong business acumen. Without strong business knowledge, a data scientist may not be able to discern the problems and potential challenges, which might hinder the growth of the organization.
Assessing with a Strong Data Intuition
Possessing a strong data intuition is quite crucial for data scientists. Valuable insights are not always visible in large data sets. Besides, a knowledgeable data scientist should have a strong data intuition and should know when to look beyond the surface for insightful information.
