The decision science industry has always been an important pillar in driving evidence-based strategies, encouraging innovation, and ensuring businesses remain adaptive. Yet there’s a significant gap between the appeal of this field and the ground reality freshers face.

“We’re not looking for fresh graduates”- sounds familiar, right?

Despite the increasing demand for decision scientists, freshers’ struggle to find an ideal position remains constant. There are always talks about how glorifying a career in decision science could be. However, the other side of the story—the challenges and hurdles—often remains untouched.

No matter how great your educational background is, unless you have some hands-on experience or are exceptionally talented, you’re likely to have a hard time landing your dream job as a fresher. But what’s the reason behind it? Let’s figure it out!

6 Reasons Why Freshers Struggle with Getting a Decision Science Job

There are multiple reasons why recruiters refrain from hiring freshers for a decision science job, including:

Lack of Practical Experience

Despite academic qualifications, freshers often lack hands-on experience with real-world problems. They may encounter multiple challenges as they weren’t well prepared before. On the other hand, companies often prefer candidates who have demonstrated their skills in a professional or applied context. 

These candidates will likely understand how to deal with complex scenarios and contribute immediately without a steep learning curve. They understand that no job is without its hurdles and possess the grit to overcome the challenges professionally.

Skills Gap

What’s taught in educational institutions may not always match the current demands of the science industry. Academics rarely focus on the required skillset for a decision science job. Moreover, the tools and methodologies in this industry progress rapidly. 

However, this may also lead to restraining academia from keeping pace with these innovations. Freshers might lack proficiency in the latest tools, technologies, or methodologies used in the industry if they fail to keep pace with the advancements. While they may have a strong foundation in theoretical concepts, they might not acquainted with the latest industry-specific tools and technologies.

Insufficient Networking

Here’s a secret: in the corporate world, who you know is equal to what you know. Networking opens doors to opportunities that might not be visible or accessible otherwise. Many positions, especially the coveted ones, filled through referrals and internal recommendations. 

Freshers, due to limited professional exposure, often possess restricted networks. This limitation can hinder their access to numerous opportunities. That’s why it’s crucial to build professional relationships from an early age.

Limited Understanding of Business Context

Decision science requires understanding the business context in which data-driven decisions are made. Freshers, coming straight from academia, might have a deep understanding of methodologies but may lack the ability to apply them in a business context. 

And with no surprise, this is one of the biggest reasons why recruiters opt for experienced professionals as they are equipped with knowledge of the complexities, work ethics, and practical understanding.

Ineffective Job Search and Interviewing Skills

Job hunting is no joke. You can’t search for a couple of days, apply, lose, and sit. To grab a decision science job, extend your job search to multiple platforms. Check offline forums, ask for advice from your acquaintances, and apply with a winning mindset. 

From having solid academic and technical proficiency to building a resume that speaks for your abilities to effective self-presentation during interviews, everything plays an equally important role. 

Being new to the market, freshers often overlook these aspects, which might lead to missed opportunities. Build a brilliant resume and portfolio, prepare for interviews, and seek guidance whenever needed.

High Competition in the Entry-Level Segment

As the appeal of decision science grows, more students and professionals are transitioning to the field. A vast pool of students graduate in this field every year. This increased influx means a higher number of applicants for entry-level positions. 

As a result, freshers find it tough to stand out. To rise above the competition, applicants must stay competent while developing a unique professional identity. They must focus on acquiring additional certificates, doing internships for better learning, and participating in other related projects.

Tips to Land a Decision Science Job

We now know that landing a decision science job can be a tough grind. If you’re dedicated enough, you’ll get there. Here are some tips to help you with your job hunt:

• Plan: Before you start your job hunt, determine your future goals. Where would you like to see yourself in 10 years? What are some companies you’d love to work for?
• Get prepared: You are now done with determining achievable goals. Get started and hone your skills. Expand your resume by learning additional relevant skills, taking courses, and doing internships.
• Build an impressive, tailored resume: If you’re applying for all the jobs at the same time, it’s high time for you to understand the importance of creating tailored resumes for each job you apply for. Job seekers with professionally tailored resumes have a 68% chance of landing a job within three months.
• Network, network, and network: Your network determines your net worth. Personal and professional connections account for 85% of job placements. Build a solid network with professionals alike and see for yourself how you end up getting better work opportunities.
• Seek guidance: Don’t hesitate to get help. If there’s a doubt, ask it out in your network. You never know when advice and insights from other seasoned professionals might help you.
• Win the battle of interviews: Only 35% of job candidates come fully prepared for their interviews. Your interview weighs more than you think. Get prepared for it. Research common questions about the company you’re applying for. Don’t forget to show the interviewers what makes you the best fit.
• Follow-up: So, it’s been days since you heard back from a company; don’t sit and relax. Follow-up.

Wrapping Up

There’s no doubt that most freshers struggle with getting a decision science job. However, it’s also true that none of them get hired. Companies often onboard new graduates as trainees. However, new businesses often can’t afford the luxury of training recent graduates. These startups need immediate results and find the onboarding of green talent time-consuming.

That’s why most recruiters lean toward hiring experienced candidates. Most HR agencies rarely prioritize fresh graduates since they aim to cater to their client companies’ immediate needs. The way forward for freshers is evident: pursue certifications, secure internships, acquire new skills, and stay informed about the latest industry shifts and methodologies.

FAQs

How difficult is it to get a job in decision science?

Given the required skills and approach, it’s not difficult to get a decision-science job. Follow the right approach:

• Take additional courses.
• Do internships for real-world experience.
• Stay updated with innovations.
• Keep trying for better opportunities.

What is a career in decision science?

There are multiple careers in decision sciences, including business analyst, software developer, data scientist, technical analyst, data analyst, and product analyst, among others.

How much does a decision scientist make a year?

The salary of a decision scientist ranges from 6-14 LPA. They may also get compensation of up to 4 lacs.

Does a decision sciences job involve coding?

Yes, decision science jobs involve coding. However, proficiency depends on the level of job you’re opting for.

What is decision science coding?

The decision science job requires a basic level of coding. For specialized roles in the decision science industry, such as a software developer, you might need to have a good grasp of coding.