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Career in Decision Science: Ultimate Guide [2024]

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21st Sep, 2022
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Career in Decision Science: Ultimate Guide [2024]

For decades now, data has been sprinting its way up towards the leading edge of businesses. With the availability of sophisticated storage systems, it is now possible to store huge amounts of data generated by sales, customer interactions, and digital experiences. Mechanisms for easy integration of disparate systems, have ensured that enormous volumes of data are continually flooding the business world.

Data technologies have managed to tame this data into actionable insights. However, data is going to continue to spawn in the future. If exploited efficiently, massive repositories of data can provide a huge opportunity for businesses. This is where decision science comes in. 

Decision science requires the ability to embrace data and utilize it in a manner that can help stakeholders arrive at critical business decisions. Utilizing data effectively to make informed business decisions translates to making intelligent inferences from data, creating effective stories, identifying relevant challenges, and then applying this knowledge correctly to the right set of problems in the business world.

career in decision science involves creating solutions based on sound fundamentals of probability, forecasting, experimentation, and computational expertise.

There is big importance for decision sciences in today’s times. The judgement gets improved with the help of decision sciences. There are various steps involved in a decision making such as understanding the problem, working with data, utilisation of tools, and gaining insights.

Skills Required by Decision Scientists

Decision scientists require a combination of certain indispensable skills, which they use in collaboration to extract value from data and solve problems. These skills include the ability to use advanced knowledge of mathematics to understand patterns and trends. Then, statistical science helps to perform technical analysis of data based on patterns and trends.

Machine learning helps to assess possibilities galore and make predictions without human intervention. Further, decision scientists require business acumen, so they can perform an astute analysis of critical challenges and make important decisions to tackle them.

They play a very important role in using the data extracted from small pockets that exist in silos and assembling the chunks together, using the knowledge of business dynamics coupled with intuition and far-sightedness to create the big picture. In short, decision scientists are artists who combine the various sciences of math, technology, and business for doing their job.

These skills are useful in the decision science job and help in providing accurate solutions. The decision scientists analyze the data pertaining to the business problem in order to come up with solutions that aid in the decision-making.

Read: Data Science vs Decision Science

Role of Decision Scientist in Various Industries

The expertise of decision scientists is useful in many industries. These include driving sales in the retail industry, providing value to the banking industry, transforming the aviation industry, contributing to the healthcare industry, transportation, communication, education, and so many more. The kind of work that one can expect to do is described using the examples of the retail and banking sectors.

1. Retail

As a decision scientist in the retail industry, you will see yourself using data for developing pricing strategies, discount techniques, and sales tactics. You will determine the right price points that would be favourable to a retail store and will contribute to the increase in revenue.

Similar contributions can be made in the areas of vendor management, inventory management, and store planning to arrive at important decisions such as the kinds of products that should be displayed together depending on the behaviour of consumers and their triggers for impulse purchases. Not only this, but you will also see yourself using trends in social media to analyze the interests of your customers and conducting marketing campaigns to drive sales.

There are various advantages to using decision sciences in the retail business. The store layout can be planned using decision sciences. The planning of store layout would help in maximising revenue by analysing the locations, infrastructure, departments, etc.

Decision sciences help the stakeholders in finding the answers to pertinent business questions that eventually lead to better growth. The involved questions could be related to the department which department is likely to produce higher traffic or on categories, which category is likely to produce higher revenue and would produce higher impact.

Sales forecasting is another advantage of decision sciences. Historical data along with the prediction of trends, patterns, or preferences help in inventory management and drive sales higher. Stock management happens very smoothly and accurately. The stocks can be analyzed and handled in case of excess or shortage of stocks. 

Another very important advantage of using decision science in retail is vendor management. Vendors are very important in the retail business and so does the monitoring and time management of delivery. Decision sciences help in maximizing the delivery output and avoiding any delays that could negatively affect business operations. 

Another important application of the decision sciences is the analyzing of customer behavior, pricing analysis, analyzing of marketing strategies, workforce analysis, fraud detection, etc.

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2. Banking

In the banking industry, decision scientists use information about customer data and customer trends to categorize their clients. Based on customer lifetime value and other relevant factors, you will use predictive analysis to personalize services and products for diverse groups of your clients. This will also involve strategizing personalized marketing initiatives and relevant interactions to acquire as well as retain customers. Nevertheless, it will involve contributing towards designing products that can help achieve business growth.

Similarly, decision scientists play a major role in the areas of fraud prevention, and risk mitigation resulting in banks saving a huge amount of money. Huge customer data can be leveraged to understand, for example, the probability of fraud even before it is committed or the chances of default on payments right at the stage of handing loans out. 

Based on how customers in a specific group use technology, decision scientists ensure investments to optimize the development and use of appropriate technological systems to derive value. Demographics play an important role in this area. For example, in a specific region where there is a large population of young people who use their mobile phones for payments, a sound business strategy may require spending on the development and maintenance of a mobile application for the bank. 

However, a different group of customers, who do not have expertise in technology, are probably retired and have time and may prefer personal interaction. Serving this group may mean the deployment of relationship management personnel to create satisfied customers and win brand loyalty. This may further extend to creating specialized products for a group that is highly likely to invest in specific financial products, thus promoting cross-selling.

Must Read: Data Science Career Path

Top Data Science Skills to Learn

Career Options in Decision Science

You may be familiar with technology or may have had a start in a field that is entirely different, yet you can work your way in the field of decision science. Here are the various career options that you can explore:

1. Business Analyst

Business analysts conduct initial research to understand a customer’s business. They form crucial links in the chain of exploring requirements and pain areas of a customer’s business. They perform an end-to-end analysis of business processes and workflows. Then, they convert this information into a language that is easily understandable by technical users and software architects who further create designs and develop software to meet the customers’ expectations.

The business analysts are majorly responsible for identifying the problems and driving the solutions for them. They are responsible for collecting data, analysing, and deriving actionable insights. 

The business analysts are required for working closely with the stakeholders to identify and achieve the business goals. With the aid of their expertise, they are able to create business models that are beneficial to the business. 

Moreover, other major responsibilities of a business analyst are testing, team management, sorting out business problems, documentation, exploring the business possibilities, presentation, visualisation of insights, etc. BBA decision science students can become business analysts provided they are aware of the appropriate tools and techniques to perform the analysis. 

Skills Required by Business Analysts

Business analysts must have excellent communication skills. As a business analyst, you will need to build a fantastic relationship with customers. You will need to ask a lot of relevant questions to be able to find out what exactly a customer needs. Next, you will set up numerous meetings with your technical team to ensure what they build concurs with what the customer has in mind. You will also need to understand how to document business flows and build prototypes in the form of sketches and wireframes.

Some of the skills that are required from a business analyst are mentioned below-

  1. Knowledge of business analyst tools
  2. Interpersonal skills
  3. Business acumen
  4. Analytical skills
  5. Organisational skills
  6. Project Management
  7. Risk Management
  8. Communication skills

Salary Earned by Business Analysts in India

On average, a business analyst or decision science analyst earns compensation of 7.0 lakhs per annum. The average range for a business analyst is 3.0 lakhs per annum to 15.0 lakhs per annum (Source). The salary could be higher owed to various factors such as location, skill sets, experience, etc.

2. Software Developer

Software development requires creating software to enable business processes and workflows.

The discipline requires understanding requirements, creating high-level and detailed designs for a project, creating software, and finally testing the code to meet specific business requirements of a customer. Software engineering requires the use of programming languages and various tools, for example, Git, GitHub, IntelliJ, etc. As a software engineer, you will also need a thorough understanding of software architecture and knowledge of backend and front-end development techniques.

The software developers are required to design, research, and management of software programs. They are required for testing and running algorithms that help the organisation.

Additionally, they are responsible for identifying the components and integrating the modifications to solve the business problems. The software developers are also responsible for troubleshooting, and debugging the problems. 

Decision sciences help the software developers to deploy the new development, categorise the development, and debug and troubleshoot the problems according to the business requirements. With the right attitude and skillsets, a good career reboot with decision sciences can take place. 

Skills Required by Software Developers

Software developers require expertise in programming languages, experience with a database, mathematical prowess, problem-solving skills, attention to detail, ability to work in a team and collaborate.

The following skill sets are useful in software development-

  1. HTML
  2. CSS
  3. JavaScript
  4. Node.js
  5. Backend development
  6. React
  7. AWS
  8. Analytical Ability
  9. Business Acumen
  10. Time Management

Salaries Earned by Software Developers in India

On average, the software developer procures a salary of 5.0 lakhs per annum. The average salary range is from 2.2 lakhs per annum to 12.6 lakhs per annum (Source). The salary could be higher due to various factors like location, experience, seniority level, etc.

Must Read: Data Science vs Decision Science: Which One You Should Choose?

upGrad’s Exclusive Data Science Webinar for you –

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3. Data Scientist

Data scientists automate manual processes. They identify the correct sets of data for analysis and use statistical methods of data analysis for visualizing, classifying, and segregating data. Data scientist wears multiple hats for their work, including that of a software engineer, data analyst, business analyst, etc.

Data scientists are highly in demand due to the level of expertise they bring to the company. The data scientists are responsible for identifying the business problems and help in identifying the problems, patterns or trends. They are also responsible for proposing solutions to the problems.

There are various techniques and methods that data scientists include in the course of their work such as data mining, merging, extraction, interrogation, interpretation, etc.

Data scientists are also required to develop hypotheses, make inferences, and analyze trends. The professionals are required to utilize their skill sets in almost every domain such as healthcare, banking, education, e-commerce, transport, manufacturing, etc. 

Skills Required by Data Scientists

Data scientists should know how to work with Statistics. They should know at least one programming language, for example, R or Python. They should be able to perform data extraction, transformation, and loading, preferably using ETL tools. Data scientists should be able to work with data wrangling and data exploration, data visualization, and machine learning.

Some of the skills required from a data scientist are mentioned below-

  1. Data visualisation
  2. Probability
  3. Statistics
  4. Data wrangling
  5. Database management
  6. Cloud computing
  7. Machine learning

Salaries Earned by Data Scientists in India

On average the data scientist earns compensation of 10.5 lakhs per annum. The average salary range for a data scientist is from 4.5 lakhs per annum to 25.3 lakhs per annum (Source). 

4. Data Analyst

Data analysts gather information from various sources and query data to obtain information. They make joins, combine data, and present it as requested for various data requests.

Data analysts are responsible for the collection, organization, and interpretation of statistical data. They are also responsible for scrutinizing the data and helping the business manage its data. 

The data analysts are responsible for utilizing their techniques and generating reports. They are also responsible for acquiring the data and analyzing or identifying the trends. 

Skills Required by Data Analysts

Data analysts should be able to work with database tables to collate data and create reports. You should be able to use tools like SQL and PostgreSQL and dashboard tools such as Tableau, PowerBI, and so on.

Salaries Earned by Data Analysts

On average data analysts procure a salary of 4.3 lakhs per annum. The average salary range from 1.9 lakhs per annum to 11.5 lakhs per annum (Source).  The decision science MBA could help in procuring higher career growth. 

Read our popular Data Science Articles

Conclusion

There are various paths to the role of a decision scientist. You can start from any of these roles. Help is available in the form of various online courses. Hope this article helped you explore the career that you want to choose.

Learn data science courses from the World’s top Universities. Earn Executive PG Programs, Advanced Certificate Programs, or Masters Programs to fast-track your career.

Profile

Rohit Sharma

Blog Author
Rohit Sharma is the Program Director for the UpGrad-IIIT Bangalore, PG Diploma Data Analytics Program.

Frequently Asked Questions (FAQs)

1What are the skills required for decision science?

Decision Science requires one to be well versed with a certain combination of skills in order to excel in it. You must be able to use advanced knowledge of mathematics to understand patterns and trends.
A deep understanding of statistical mathematics helps you to perform technical analysis of data based on patterns and trends. Apart from that, Machine learning plays a crucial role in decision science as it enables the machines to access the future outcomes of a certain scenario.

2What is decision science?

Decision science involves the study of various subjects including a business-oriented approach, mathematics, analytical skills, technical skills, design skills, and overall problem-solving skills. All these skills make up a decision scientist who is one of the most valuable assets of a company.
As a data scientist, you will be interacting with senior managers and will be responsible to partake in important decision-making processes. Your responsibility will be to analyse a business problem using your business and technical skills, and help managers take essential decisions for achieving goals.

3How does data science differ from decision science?

The key difference is that a data scientist extracts information or insights from the data and a decision scientist utilizes these extracted insights to help make essential business decisions. Both of them use skills such as technical skills, mathematics, and analytical skills, but their roles differ from each other to a larger extent.
In broader terms, data science deals with creating visuals and reports from the data whereas decision science deals with helping organizations use these reports.

4What can you do with a degree in Decision Science?

Decision Science is highly useful and relevant in various fields. The decision sciences are useful in the management, healthcare, public, private, and non-profit sectors, etc. The professionals can make a successful career in any field of their choice coupled with relevant skill sets.

5Why is Decision Science important?

Decision Science is important for various reasons. It is useful in understanding and developing a framework that helps in analysing and arriving at the solutions in a much more accurate manner. The decision sciences are also responsible for understanding how decisions are made, why are they made and how to arrive at better conclusions.

6What is decision science approach?

Decision sciences is a scientific approach for arriving at better conclusions. There are various steps that are involved in the decision-making process, such as identifying the problems, gathering information, running algorithms, and providing solutions.

7Does decision sciences involve coding?

Yes, decision science involves coding. Decision science does not necessarily involve deep-rooted knowledge.

8What is the salary of a decision scientist?

Decision science is a highly paid job. On average the salary of a decision scientist is 7.3 lakhs per annum. On average the salary bracket ranges from 6.3 lakhs per annum to 9.0 lakhs per annum. The salary bracket may differ owing to various factors such as location, skill set, company, experience, etc.

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