Table of Contents
Introduction:
In today’s fast-growing digital world, engineers and professionals looking to change careers are searching for ways to break into data science. The demand is huge, but so are the challenges. Many freshers hesitate to apply because job postings often highlight advanced skills, leaving them unsure about qualifications. This blog will guide you step by step, so you can confidently land entry level data science jobs. Whether you’re an engineering graduate ready to transition or a career switcher seeking growth, this path is open for you if you prepare wisely.
What You’ll Learn
- Overview of entry level data science jobs
- Typical entry level data science job requirements
- Key junior data scientist roles beginners start with
- Insights into companies hiring entry level data scientists
- Specific strategies for engineering graduates and career changers
- Resources and training pathways to boost your chances
Why Entry Level Data Science Jobs Are in High Demand
Businesses across the world are using data to drive decision-making. Every digital transaction, click, or purchase creates information that can be analysed. For this reason, organisations offer multiple data science fresher jobs each year to build a solid resource pool of talent.
Opportunities for Engineering Graduates
Engineering graduates are especially sought-after since they already understand analytics, mathematics, and coding. Their mindset makes adaptation into junior data scientist roles faster.
Why Career Switchers Are Welcome
Career switchers bring diverse perspectives to the table. For example, a finance professional entering data science can work on risk modelling or investment analytics. Companies are eager to train such fresh minds for entry level data science jobs.
Build your career step-by-step!
Entry-Level Data Science Job Requirements
Most employers have a fixed set of skills they expect. As someone aspiring for fresher or junior data scientist roles, knowing these helps target your preparation.
Technical Knowledge Required
- Basics of statistics, probability, and linear algebra
- Knowledge of Python, R, or SQL
- Data cleaning, preprocessing, and exploratory analysis
- Familiarity with data visualisation tools like Tableau, Power BI, matplotlib, and seaborn
Essential Soft Skills
- Problem-solving approach to data challenges
- Strong communication for converting numbers into insights
- Collaboration with teams across domains
- Continuous learning mindset
Employers understand that not everyone knows everything. If you can show eagerness to learn, you can still succeed in entry-level data science jobs.
Popular Junior Data Scientist Roles
When you are just entering, your job title might vary depending on the company structure. Common profiles include:
Data Analyst
Focuses heavily on examining raw datasets, cleaning them, and building dashboards. It is one of the most common data science fresher jobs.
Business Analyst
Acts as a bridge between numbers and decisions. Business analysts often prepare presentations and reports that directly support growth strategies.
Junior Data Scientist
Involves small-scale problem-solving using statistical models and machine learning techniques. These junior data scientist roles allow freshers to grow quickly.
Machine Learning Intern/Associate
Supports machine learning model building, usually under the guidance of senior scientists.
Companies Hiring Entry Level Data Scientists
India’s job market is booming in this sector. Here are some popular industries and employers:
IT and Consulting Giants
- Infosys
- TCS
- Wipro
- Deloitte
- Accenture
Product and E-commerce Companies
- Amazon
- Flipkart
- Paytm
- Zomato
- Swiggy
Startups and FinTech Firms
Early-stage companies are a hotspot for data science fresher jobs because they need fast insights to scale.
These companies hiring entry level data scientists often shortlist candidates who have a project portfolio or internship listed in their profiles.
Career Path for Engineering Graduates
As an engineer, you already have the analytical foundation required. Now, it’s about approaching data science strategically.
Steps for Engineers to Transition
- Reinforce statistical and mathematical foundations
- Practice extensively with Python or R
- Build real-world projects on GitHub
- Showcase examples of solving business problems using analytics
Even simple visualisation reports or Kaggle competition entries can serve as proof of ability for entry level data science jobs.
Turn Data Skills Into Opportunities!
Transitioning as a Career Switcher
Career switchers often underestimate their background, but transferable skills make a big difference.
How to Begin
- Enrol in certificate-level data science training for structured learning
- Highlight transferable strengths such as Excel, problem-solving, or client-facing experience
- Apply first to junior data scientist roles or business analyst roles
- Network via LinkedIn or professional communities
For instance, a retail manager shifting to data science can leverage expertise in demand forecasting using data tools.
How to Prepare for Entry Level Data Science Jobs
Success depends on structured preparation. Here’s how to organise your steps:
Build Your Technical Toolkit
- Python/R coding portfolio
- SQL queries and database handling
- Presentation-ready dashboards
Work on Projects
- Analyse sales data for retail
- Forecast revenue for e-commerce
- Predict churn in telecom data
Internship and Networking
Even unpaid internships add immense value. Attending hackathons or seminars also boosts visibility when targeting companies hiring entry level data scientists.
Training and Courses for Freshers
Several institutes in India offer targeted training for freshers and career switchers. Choosing the right training can improve your practical exposure.
What to Check Before Joining a Course
- Industry-relevant curriculum aligned with entry-level data science job requirements.
- Portfolio-building projects
- Placement support or tie-ups with recruiters
- Trainer background and practical experience
When evaluating courses, look for programs that offer practical, hands-on learning and strong placement support. For instance, institutes like Systech Group provide structured data science training with project-based learning, mentorship from industry professionals, and connections to potential employers. Choosing such programs can significantly improve your readiness for entry-level data science roles.
Which Course Suits You Best?
Conclusion
Breaking into entry level data science jobs doesn’t have to be overwhelming. Both engineering graduates and career switchers can succeed with the right skill set, projects, and mindset. Companies across IT, e-commerce, and consulting are actively looking for freshers prepared to solve data problems. Start preparing today with projects, training, and networking, and open doors to long-term success in this exciting domain.
FAQs
What qualifications are needed for entry level data science jobs?
Usually, a degree in engineering, statistics, or IT helps, but companies also consider candidates from other fields if they demonstrate skill readiness.
Are data science fresher jobs available in non-IT fields?
Yes, industries like healthcare, banking, and e-commerce are also offering data science fresher jobs.
What are common entry level data science job requirements?
Knowledge of Python, statistics, and SQL are the most demanded entry-level data science job requirement.
Do companies hiring entry level data scientists consider career switchers?
Yes. Many top companies hiring entry level data scientists welcome career switchers who complete training and showcase projects.
How do junior data scientist roles differ from senior roles?
Junior data scientist roles involve executing analysis under guidance, while senior roles include project planning and advanced modelling.