Internship Experience at ICICI Bank
ExperiencesMakthala Susank
Follow Susank on his internship journey at ICICI Bank.
Company Overview
ICICI Bank is one of India’s leading private sector banks, offering a diverse range of financial services across retail, corporate, and investment banking. The bank is also known for its growing focus on technology, analytics, and innovation in financial services.
I had the opportunity to pursue my two-month summer internship at the Hyderabad office, where I worked with the Data Science and Analytics group.
How I Got There
The selection process for ICICI was rigorous and multi-layered.
- Application process: Candidates were shortlisted primarily based on their resume and academic performance (CGPA).
- Behavioural round: An online round was conducted—not eliminative—mainly to assess organisational fit.
- Interview process: The technical and HR rounds were conducted simultaneously. The panel mostly focused on projects mentioned in my resume, which were based on machine learning, deep learning, and NLP.
ICICI also recruits interns into other verticals such as model validation, core technical teams, and analytics, depending on the candidate’s background and interests.
Roles and Responsibilities
My main project during the internship was the Preparation of a Sourcing Quality Dashboard, aimed at providing data-driven insights into sourcing efficiency and quality.
The role allowed me to combine business understanding with technical expertise. While I applied tools like Python, SQL, Excel, and Machine Learning, I also learned Power BI from scratch to design interactive dashboards that could communicate insights effectively to stakeholders.
Mentorship & Learning
Since I was new to the banking sector, the guidance of my mentor played a crucial role. He not only clarified banking terminologies and domain-specific concepts but also emphasized thinking like an analyst, going beyond coding to derive meaningful business insights.
Through continuous feedback and support, I learned how to align data science methods with real banking use cases, applying statistical techniques and visualization tools to solve problems that mattered.
Work Environment & Culture
The internship at ICICI demanded both professionalism and discipline:
- Office timings were from 9 AM to 5 PM.
- Punctuality and formal dress code were strictly followed, reflecting the professional banking culture.
- Working days included Saturdays as well, except the 2nd and 4th Saturdays (in line with bank policy).
- Interns were expected to use their own laptops and internet connection, ensuring data privacy and security.
The environment encouraged independence—while guidance was always available, interns were expected to take initiative and deliver outcomes responsibly.
Key Takeaways
- Learned Power BI and improved my skills in Python, SQL, Excel, and Machine Learning.
- Understood how dashboards can directly aid in business decision-making.
- Gained exposure to banking terminologies, compliance aspects, and statistical methods specific to the financial domain.
- Developed professionalism by adapting to the corporate culture of punctuality, ownership, and self-discipline.
Advice for Future Interns
- Preparation: Strengthen resume projects, especially in data science, ML, and analytics, as interviews focus heavily on them.
- During internship: Be proactive, ask questions, and don’t hesitate to seek help from mentors.
- Work culture: Maintain discipline in time management and dress code, as these are taken seriously.
- Technical readiness: Be open to learning tools like Power BI or Tableau, which are widely used in analytics.
Final Thoughts
My summer at ICICI was a rewarding journey where I not only applied my technical knowledge but also gained a strong sense of how data science integrates into the banking sector. The exposure to real-world projects, combined with mentorship and professional culture, made it a highly enriching experience.
This internship not only enhanced my technical skills but also shaped me into a more confident and industry-ready data science professional.
