Data Science Career – A Comprehensive Guide

Data science is an evolving field and one of the most promising professions in the world today. It is a field where advanced analytics methods and statistical tools are applied to datasets to extract valuable information.

The insights are useful for the organizations and help them in planning and decision-making. It gives a competitive edge to the businesses helping them improve their products and services, make expansion plans, customize their marketing strategies, and more. Its impact is far-reaching and affects almost all aspects of business operations.

Data science incorporates various disciplines, including software programming, mathematics, statistics, predictive analytics, data mining, data preparation, machine learning, and data visualization. A data science training in California is the best way you can kickstart your data scientist career.

Why Are Data Scientists Important?

Data is growing exponentially. Every day approx. 2.5 quintillion data bytes are created. It is projected that by 2025, the data will reach 180 zettabytes. This has made data science extremely important as it is the only way data can be decoded and utilized for various purposes.

Businesses across sectors look for data scientists who can help them achieve their business goals. Whether finance, healthcare, manufacturing, logistics, marketing, retail, or security, most industries today require data scientists to make sense of the data.

The demand for data scientists has risen in the past few years due to the many benefits data science offers. Data scientists hunt through the structured and the unstructured data and perform various functions to derive meaning from it.

A data science professional can wear many hats and work as a data analyst, data architect, BI developer, data engineer, machine learning engineer, data visualizer, etc. All these professions have skills that come under the umbrella term’ data science.’

Industries Where Data Scientists Are Highly Demanded

If you have done data science training, you can work in nearly any industry of your choice. The blend of skills that data scientists possess makes them useful everywhere. Let us narrow down some industries where data scientists are highly demanded, and you can choose to make a career in.
  • Healthcare: Modern healthcare is highly dependent on data, making it a great field for data scientists. Big data help provide quality care, improve healthcare facilities, and is useful in image analysis, diagnosis of medical conditions, planning treatment, and medical research.
  • Insurance, Finance, and Banking: It is unarguably the most demanded industry for data scientists. Data science aids in managing financial risks, detecting fraudulent transactions, and portfolio management. For this field, you will require at least a few years of experience in the finance sector. It also helps block security threats and cyber-attacks.
  • Education: Data science has proved to be highly effective in helping students improve their academic skills. Similarly, it has helped educators analyze student’s requirements, improve curriculum and innovate teaching methods. By gauging the students’ and teachers’ performance, data science helps institutions understand the underlying problems in the education system and tackle problems such as dropout rates.
  • Utilities and Energy: The transformative powers of data science are quickly changing the utilities and energy industry. Data science has been extremely useful in reducing costs and finding unconventional sources of energy. In addition, it has helped improve productivity, avoid accidents, reduce power outages, and more.
  • Media and Communications: Media giants like Netflix, Spotify, Amazon Prime, YouTube, etc., are already leveraging the benefits of data science. It has helped them offer customers tailored recommendations, providing them the content they would like. Besides, the media and communication industry also relies on data science to improve the company’s media and entertainment initiatives.
  • Retail: Data science helps the retail industry comprehend buyer’s patterns and behaviors, market trends and provide them personalized suggestions and options.
  • Manufacturing: Many manufacturing industries are incorporating data science for streamlining the manufacturing process, prevent equipment breakdown in the plant, demand forecasting, inventory management, product development, price optimization, and warranty analysis.

Education Needed To Become A Data Scientist

Before you opt for any specialized data science training, you must have a Master’s or a Ph.D. degree. If you have it, great! But graduation is also good enough to enter into the data science profession. A degree in the following disciplines will increase your chances of landing a data scientist job.
  • Economics and social sciences, including economics, business studies, finance, history, politics, philosophy, psychology, and marketing and management;
  • Natural science, including chemistry, physics, and biology;
  • Statistics and mathematics;
  • Computer science;
  • Engineering;
  • Data science and analysis, including machine learning.
Here you can see that data scientists come from varied areas of study. So, no matter your background, you have a good chance of becoming a data scientist. You can definitely opt for a data science bootcamp later. If you go through successful data scientists’ LinkedIn profiles, you will find that almost 43% have completed at least one data science course with 3 certificates on an average.

Skill Of Data Scientist

Data scientists are known for their robust skills and competencies in various fields. The average salary of a data scientist is $117,120/year. Data Science In Bay Area is most demanded and has the highest salaries for data scientists. Let’s look at the skills you must acquire to become a data scientist.
  • R: R is a crucial data science programming language used for data analysis, statistical analysis, and data visualization
  • Python coding: Python is the preferred programming language to implement mathematical models and concepts as it has rich libraries and packages to build and deploy models.
  • MS Excel: It is an essential requirement for all data entry tasks, useful for data analysis, applying formulae, equations, and diagrams out of massive chunks of data.
  • Hadoop Platform: It is an open-source platform used for data processing and storage of big data. Some of the frameworks/ tools you must master are Hadoop, Apache Storm, Spark, Hive, and Flink.
  • SQL database/coding: It is used for the preparation and extraction of datasets and is useful for search behavior, fraud detection, graph, and network analysis, etc.
  • APIs: You should be aware of various APIs and tools useful in accessing and understanding the data.
  • Statistics: It is a must for data scientists. You should be aware of concepts like mean, mode, median, standard deviation, and variance, various probability distributions, CLT, skewness and kurtosis, sample and population, inferential statistics, and so on.
  • Mathematics: Machine learning algorithms such as regression, time series, clustering, etc., require a very high amount of mathematical knowledge, so you must have knowledge about them.
  • Data analysis and manipulation: Data in its raw form is not comprehensible and contains many errors. You should know about data manipulation and wrangling methods such as missing value imputation, scaling, correcting data types, outlier treatment, and transformation.
  • Data visualization: You should be aware of plots like histograms, pie charts, bar charts, thermometer charts, waterfall charts, etc. These plots are extremely handy during the exploratory data analysis stage.
  • Machine learning: Machine learning is the core skill you should have. It is used to build predictive models. You can start with a linear and logistic regression model and move to advanced ensemble models like Random Forest, CatBoost, XGBoost, and so on.

Other Skills

  • Curiosity: You should have a deep curiosity to solve problems and find solutions and an out of box thinking. There should be a desire in you to understand more what data is telling you and how you can figure it out.
  • Communication: It is an essential skill that you must have. You can’t communicate what the data says without good communication skills. As it is a mid-level position, you will communicate a lot with your team and the stakeholders.
  • Business Acumen: As a data scientist, you should know how to effectively use data to fulfill the business’s goals and objectives. You should be able to offer a solution to the business problems.
Since data science is touching every aspect of business in different industries, jobs in this domain are thriving like never before. According to BLS, the growing need for data science professionals is projected to create about 11.5 million jobs globally by 2026. Besides, the World Economic Forum has predicted that data scientists and analysts would become the number one job roles by 2022.

Are you looking to kickstart a career in data science? The SynergisticIT data science program will help you gain data science skills with a project-based curriculum designed by industry experts. Build your portfolio and master the skills to pave a career as a successful data scientist.

Also, Read This Blog: What Is Data Science In Simple Words?
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