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Data Science Career Paths: Where to Start Your Journey


Good strategies and decisions are crucial for every business's growth. In a data-driven world, decision-making depends on the useful use of data for the business. These insights can help firms achieve their goals, but the problem is that the volume of raw data is growing exponentially daily.


It has resulted in a surge in requirements of data experts or professionals who can turn this into meaningful data. This has led to the rise of data science as one of the most demanding fields in the tech sector. Data science jobs are rewarding, engaging, educational, future-focused, and fulfilling.


According to QuantHub, the Data Science field has grown by 650% since 2012. Data is generated at an exponential rate, and businesses will continue to seek different ways to utilize this data for transformational purposes to maximize their profitability. Let’s understand what are the possible data science career paths that interested candidates can choose and how you can begin your journey.



Which Career Paths Are Available to Data Experts?

There are numerous career pathways in data science, each with special prospects. It's common to be unsure about the precise duties involved in certain professions or the best course of action for you. To help make things easier, we've divided the primary roles into three broad categories.


  • Data Analysts (Entry Level Positions)


    Data analysts mainly focus on basic data interpretation and report generation. They also visualize data to help firms see trends and make wise decisions. To perform these tasks, they often use simple statistical analysis software, Excel, and SQL. A bachelor's degree in a related field—such as computer science, statistics, or mathematics—is typically the minimal prerequisite.


    Average Salary: $69,000 - $100,000/year


  • Junior Data Scientist (Entry Level Position)


    Another entry-level position that performs basic statistical analysis, data cleansing, and machine learning models on smaller data sets. A bachelor's or master's degree in data science, machine learning, or a similar discipline is typically required to be eligible.


    Average Salary: $85,000 - $120,000/year


  • Business Intelligence (BI) Analyst (Entry Level Position)


    BI analysts can work in entry-level or early-career roles. They typically work with key performance indicators (KPIs) and dashboard reporting and depend on data analysis to help achieve organizational objectives. Eligibility typically requires a bachelor's degree in information technology, data science, business analytics, or a related discipline.


    Average Salary: $79,000 - $120,000/year


  • Database Administrators (Mid-Level Position)


    As the name suggests, database administrators are responsible for maintaining the database infrastructure, ensuring databases operate efficiently and seamlessly. It usually involves monitoring performance, managing access, and analyzing the security to prevent any data breach. They design and implement database solutions, optimize the performance through fine-tuning, and oversee data storage and retrieval.


    Average Salary: $96,000 - $159,000/year


  • Data Architect (Mid-Level Position)


    Data architects are responsible for designing and developing data infrastructures required for effective data-driven decision-making. Like architects, data architects are builders, creating frameworks and designing robust and industry-regulated data models that support business operations. They build data strategies to ensure the integrity and usability of the organization’s data systems.


    Average Salary: $149,000 - $229,000/year


  • Machine Learning Engineers (Mid-Level Position)


    These professionals work with real-world scenarios to optimize and apply machine learning models. Prerequisites include programming experience and familiarity with machine learning frameworks and libraries. A machine learning engineer's job responsibilities include integrating external datasets to enhance model performance, building APIs to integrate ML models, and fine-tuning the existing ML models.


    Average Salary: $126,000 - $221,000/year


  • Lead Data Scientist (Senior-Level Position)


    Lead data scientists oversee and manage data science teams. These professionals ensure that all project insights are easily understood by all parties involved. The three most crucial qualities are a wealth of experience, effective leadership, and in-depth domain knowledge.


    Average Salary: $118K–$206K/yr


  • Chief Data Officer (Senior-Level Position)


    The general data strategy of a business is overseen by chief data officers. The CDO is necessary in order to handle data as a strategic asset, use it to guide business choices, and increase productivity. A bachelor's degree in data science, computer technology, business administration, or a related field is typically required to be qualified. Having a master's degree or MBA and many years of data management experience might sometimes increase this necessity.


    Average Salary: $111,000 - $420,000



Why Would You Want to Work in Data Science?

If you are still confused about whether you should choose this field or not, let me help. Everyone is aware of the rising demand for skilled data specialists across several industries, including technology, sales, eCommerce, banking, and healthcare. Not only this, there are many reasons. The following is a list of factors that can help you make your decisions:


  • Competitive Salary: One of the basic requirements of a working person is the salary. You will be happy to know that data experts get some of the best salaries among all specialists in the technical areas.

  • High Demand: There are several work prospects in the rapidly growing field of data science. According to the US Bureau of Labor Statistics, the demand for data scientists is expected to witness a rise of 35% between 2022 to 2032.

  • Impactful Work: Your decisions as a data expert can affect an organization's future and growth. Thus, data specialists are crucial in finding solutions to practical issues.

  • Numerous Career Paths: A variety of jobs in data science are available, including those as business intelligence analyst, machine learning engineer, and data analyst.



How Do You Begin Your Career in Data Science?

If you are now confident enough to pursue a career in the data science field, you can get started by doing the following:


  • Learn the Fundamentals: The first thing required is knowledge of fundamentals. You must have a good understanding of mathematics, statistics, and programming to begin working in data science. For the coding part, you can start with R and Python, especially NumPy and Pandas libraries.

  • Proficiency in Data Visualization: The ability to clean and visualize data is essential for deriving meaningful insights from it. To do this, you can learn how to use Python libraries like Pandas and Seaborn or Matplotlib for visualization. Additionally, you can go to systems like Hadoop and Apache Spark for huge datasets.

  • Master Machine Learning: As you progress, look into deep learning strategies like neural networks and machine learning strategies like decision trees and random forests. Study up on common frameworks TensorFlow or PyTorch.

  • Real-World Experience with Practical Data: To gain practical experience, begin working with real-world datasets. You can search websites like Google Dataset Search, Kaggle, and the UCI Machine Learning Repository to obtain these datasets.

  • Get Certified: You can improve your credibility and employment prospects by earning a certification. Data science courses are offered by prestigious universities and companies on a variety of platforms.



Are You Prepared to Begin a Data Science Career?

The field of data science is flourishing and blooming, and the same can be expected in the future. This is because enterprises and organizations have realized the potential of data, and data science is all about techniques and technologies to extract vital information from the voluminous set of raw data.


So, if you are someone who’s interested in exploring data and how you can maximize the efficiency of the algorithms or methods to convert the raw data into statistical insights, then you must give data science a shot. You can rest assured regarding job security, earning capacity, and personal growth because data science is an emerging career option.

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Posted By

   
Akash Singh
Content Writer
16-October-2024

"A dedicated content writer, with a strong emotional intelligence."


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