How to become a Statistician without a Degree

How to become a Statistician without a Degree?

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Statistical is a mathematical branch that deals with collecting, analysing and interpreting data and presenting it mathematically. With the help of these data, statisticians tend to solve economic, social and business problems. Different industries like healthcare, insurance, banking, legal, etc., benefit from statistics hence, job opportunities in Statistics are increasing. 

By using effective statistical methods, statisticians solve business problems of the real world. It plays an important role even for research and scientific studies. Recently, the demand for statisticians has increased in the world because of the large influx of data, requiring executives to make data-driven decisions. 

If you are aspiring for a career in becoming a statistician and experience potential growth, acquire decent salary and maintain a healthy work-life balance, the job role is a perfect fit. 

Stacy is a statistician who transitioned from a mathematical background and took up the course of statistics to become an expert in the field. Her experience and knowledge in the field needs to be known and this blog, will help you to understand how to become a Statistician. 

Statistician Job Role and Responsibilities: 

Stacy feels that Statisticians play a crucial role in collecting, analysing, and interpreting data to inform decision-making and solve problems across various industries. The specific job role and responsibilities of a statistician can vary depending on the industry, organisation, and level of experience. However, she points out some common job roles and responsibilities associated with statisticians:

  • Data Collection and Preparation:
      1. Design and implement data collection methods, such as surveys, experiments, or observational studies.
      2. Clean and preprocess data to ensure its quality and reliability.
  • Statistical Analysis:
      1. Apply statistical techniques to analyse data, including descriptive statistics, hypothesis testing, regression analysis, and machine learning algorithms.
      2. Develop and implement statistical models to answer specific research questions or solve problems.
  • Experimental Design:
      1. Plan and execute experiments, ensuring proper randomization and control groups to gather meaningful data.
      2. Analyse experimental results and draw conclusions based on statistical analysis.
  • Data Visualization:
      1. Create clear and informative data visualisations, such as graphs and charts, to communicate findings to non-technical stakeholders.
  • Statistical Software and Tools:
      1. Use statistical software like R, Python, SAS, or specialised tools to conduct data analysis and generate reports.
      2. Stay updated with the latest tools and techniques in the field of statistics and data analysis.
  • Interpretation and Reporting:
    1. Interpret the results of statistical analyses in the context of the problem being addressed.
    2. Prepare written reports, presentations, and visual aids to communicate findings to colleagues, clients, or decision-makers.

Statisticians can work in a wide range of industries, including healthcare, finance, government, academia, marketing, environmental science, and more. The specific responsibilities may vary considerably depending on the sector and the organisation’s goals.

How to become a Statistician in India? 

Becoming a statistician typically involves a combination of education, training, and practical experience. Stacy has laid down a detailed guide for you to understand how to become a statistician.  Here are the steps you can follow to become a statistician:

  • Educational Requirements:
      • Bachelor’s Degree: Start by earning a bachelor’s degree in statistics, mathematics, or a related field. While a bachelor’s degree in statistics is ideal, you can also major in fields like mathematics, economics, or computer science with a strong focus on statistics coursework.
  • Master’s Degree (Optional):
      • Consider pursuing a master’s degree in statistics or a related field if you want to advance your career and have more specialised knowledge. A master’s degree can also make you a more competitive candidate for job opportunities.
  • Develop Strong Mathematical and Statistical Skills:
      • Statistics is a heavily maths-based field, so it’s essential to have a strong foundation in mathematics, including calculus, linear algebra, and probability theory.
      • Develop proficiency in statistical methods and software such as R, Python, SAS, or SPSS, which are commonly used in the field.
  • Gain Practical Experience:
      • Internships or research assistant positions during your undergraduate or graduate studies can provide valuable practical experience. Look for opportunities to work with data, conduct statistical analysis, and gain exposure to real-world applications.
  • Build a Portfolio:
      • Create a portfolio showcasing your statistical projects, analyses, and research. This can be a valuable asset when applying for jobs or graduate programs.
  • Networking:
      • Attend conferences, seminars, and workshops related to statistics and data analysis. Networking can help you connect with professionals in the field and learn about job opportunities.
  • Job Search:
      • Start your job search by looking for entry-level positions in fields such as data analysis, market research, or government agencies. These positions often serve as stepping stones to more specialised roles in statistics.
  • Certifications:
      • Consider obtaining relevant certifications to enhance your qualifications. For example, you might pursue certifications like the Certified Statistical Business Analyst (CSBA) or Certified Statistician (CStat) from professional organisations.
  • Continuing Education:
      • Stay updated with the latest developments in statistics by taking additional courses, attending workshops, or pursuing a Ph.D. if you’re interested in research or academia.
  • Specialisation:
      • As you gain experience, you may choose to specialise in a particular area of statistics such as biostatistics, econometrics, or data science. Specialisation can open up more specific career opportunities.
  • Ethical Considerations:
      • Be aware of the ethical responsibilities of working with data, especially when dealing with sensitive information. Familiarise yourself with relevant laws and ethical guidelines.
  • Soft Skills:
      • Develop strong communication and problem-solving skills, as statisticians often need to explain complex concepts and findings to non-technical audiences.
  • Stay Inquisitive:
    • Statistics is a constantly evolving field, so remain curious and open to new methods and technologies. Continuous learning is essential for long-term success.

Stacy clearly suggests that the path to becoming a statistician can vary depending on your specific career goals and interests. Whether you choose to work in academia, industry, government, or another sector, a strong educational foundation, practical experience, and a passion for working with data are key components of a successful career in statistics.

Skills Required to Become a Statistician:

Skills Required to Become a Statistician 

To become a successful statistician, Stacy points out that you need a combination of technical and soft skills. Here is a list of skills required to excel in this field:

Technical Skills:

  • Mathematics: Strong mathematical skills are foundational for statisticians. You should have a solid understanding of calculus, linear algebra, and probability theory.
  • Statistical Knowledge: A deep understanding of statistical concepts and methods is essential. This includes hypothesis testing, regression analysis, experimental design, and probability distributions.
  • Data Analysis Tools: Proficiency in statistical software and programming languages is crucial. Common tools include R, Python, SAS, SPSS, or specialised software for specific industries.
  • Data Manipulation: The ability to clean, preprocess, and manipulate data is a fundamental skill. You should know how to handle missing data, outliers, and format data for analysis.
  • Statistical Modelling: Learn how to build and interpret statistical models for various types of data, such as linear regression, logistic regression, time series analysis, and machine learning models.
  • Experimental Design: Understanding how to design experiments to gather meaningful data is vital. This includes randomization, control groups, and minimising bias.
  • Statistical Inference: Be able to draw valid conclusions from data, make predictions, and assess the reliability of your results.
  • Big Data and Machine Learning: Familiarity with big data technologies and machine learning techniques can be valuable, especially in data-intensive industries.
  • Data Visualization: Communicate your findings effectively through data visualisation tools like ggplot2 (in R), matplotlib (in Python), or specialised data visualisation software.

Soft Skills:

  • Analytical Thinking: Statisticians must be able to analyse complex problems, break them down into smaller components, and apply statistical methods to solve them.
  • Critical Thinking: Develop the ability to question assumptions, evaluate the validity of data, and identify potential sources of bias in research.
  • Communication: Statisticians often work with non-technical colleagues or clients. Being able to explain complex statistical concepts in a clear and understandable way is crucial.
  • Problem-Solving: You will encounter novel challenges regularly. Effective problem-solving skills are essential to adapt and find solutions.
  • Attention to Detail: Small errors can have significant consequences in statistical analysis. Being meticulous is important to ensure the accuracy of your work.
  • Teamwork: Many statistical projects involve collaboration with researchers, analysts, and other professionals. Being a team player and sharing your expertise is essential.
  • Ethical Considerations: Understand the ethical implications of working with data, especially when dealing with sensitive or confidential information.
  • Time Management: Statisticians often work on multiple projects simultaneously. Good time management skills are necessary to meet deadlines and prioritise tasks.
  • Continuous Learning: Stay updated with the latest developments in statistics, data analysis tools, and software by engaging in continuous learning and professional development.
  • Domain Knowledge: Depending on your area of specialisation, having domain-specific knowledge (e.g., healthcare, finance, social sciences) can be a significant advantage.

Remember that while technical skills are crucial, soft skills like communication and critical thinking are equally important for a statistician’s success. Developing a balance of these skills will help you excel in your statistical career, whether you work in academia, industry, government, or any other sector.

Statistics Career Options:

There are numerous career options in the field of Statistics that you can avail in different sectors. Following are the jobs for statistics graduates that you may opt which can help you have a lucrative opportunity: 

  • Research Scientist, Researcher 
  • Statistical Consultant 
  • Statistical Reporting Analyst 
  • Demographer 
  • Mathematical Statistician 
  • Statistical Analyst Statistician 

Salary and Demand of Statisticians:

The demand for statisticians is high in the market considering the need for conducting data analysis and research by organisations to find about industrial trends, economic conditions, etc. 

Accordingly, Stacy reveals that salary levels are quite high for those with a statistical background. For freshers, the average salary is more than Rs 5 lakhs which is quite lucrative. 

For those who want to pursue Statistics as a career choice, course fees remain quite low. This implies less than 2 lakhs for any course on statistics. 

However, the level of preparation in the courses remains quite high with immense hard work and calculations involved. While students may spend more than a year in the subject, the preparation for the entrance test is required to get admission. 


In conclusion, Stacy clearly lays down the significance of statistics in the world today which requires you to have mathematical skills and proficiency. Additionally, while the career may seem quite lucrative with numerous jobs for Statistics students, one needs to indulge in an immense level of preparation. 

Moreover, the career choices in the field of Statistics are quite tempting and one can even indulge in transitioning to more technical fields like Data Science or Data Analytics where statistics plays an important role.