# FORESIGHT (2024) | Internship at Fidelity Investments | Shubh Guwalani

Student Welfare Group, IIT Kharagpur
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1) Brief introduction and description of the offered role
Hey everyone! I am Shubh Guwalani, a pre-final year undergraduate student from the Department of Biotechnology, enrolled in the dual Degree course. I’m Interning at Fidelity Investments in Data Science domain in its AI Centre of Excellence department in the Private Investments division. This is a research and application-based role, and you will be expected to research and develop innovative solutions for the finance industry.
2) How did you get into Fidelity Investments? What was the selection procedure?
The selection procedure requires us to submit our CVs, and after a round of CV shortlisting, there are 2 Technical Interview rounds followed by an HR Interview. The company especially looks for CVs that are NLP-oriented and a little exposure to finance projects. Having an LLM project in your CV would fetch brownie points.
In the first Technical Interview round, I was asked about my projects and previous internships and to explain the detailed working and mathematical models used in the algorithms in detail. I had a project related to financial analysis using Deep Learning Algorithms, and we discussed that in detail during the interview.
In the second technical round, my coding abilities were tested, where I was asked to hardcode some of the ML algorithms, like logistic regression and LSTM, on paper (that is, without using preexisting libraries). I was asked to compare the algorithms I had mentioned in my CV on the basis of efficiency and accuracy, and there were also some questions about OOPs.
HR round was not easy. You will be required to explain your personality and will be asked situational questions, and your answers must reflect your personality. I kept the interaction more of a discussion and less of a question-answer format which helped me have an interactive interview and reflect my skills to the interviewer efficiently.
3) How to prepare for them?
Build a Strong Foundation in Statistics and Mathematics
Data science relies heavily on statistical and mathematical concepts. Ensure you have a solid grasp of probability, linear algebra, calculus, and statistical inference.
Proficiency in programming languages, particularly Python and R, is essential. Python is widely used in all ML algorithms, while R is powerful for statistical analysis. Practice writing clean, efficient code and familiarize yourself with libraries like pandas, NumPy, scikit-learn, and matplotlib.
Study different algorithms such as linear regression, decision trees, k-means clustering, and neural networks. Implement these algorithms on real datasets to understand their nuances and applications.
Participate in Kaggle competitions, work on personal projects, or contribute to open-source data science projects. These experiences not only improve your skills but also enhance your portfolio, showcasing your ability to solve real-world problems.
Master tools like Matplotlib, Seaborn, and Tableau to create compelling visualizations that tell a story with your data. Good visualizations can make complex insights more accessible to non-technical stakeholders.
Try to learn about Transformer architecture and familiarize yourself with using hugging face transformers and building customized models.
4) When did you start preparing for this role and according to you what is the ideal time for aspirants to begin their preparation?
I started preparing in my 2nd year. I started out by learning ML and DL, then did a few projects from Kaggle, and then developed industry skills by doing Internships. In my third year, I did a lot of DSA and learned theoretical concepts like OOPs, computer networks, and system design to polish my skills. The ideal time for preparation would be one year before the interview, but I have seen people prepare in around 3–4 months as well, so that depends on your commitment.
5)What difficulties did you face while preparing for this Company/Profile? How did you overcome them?
The most difficult part was staying up to date on new algorithms and models that are added almost daily and to approach each problem in a different way to get the best results. I overcame this problem by reading blogs, participating, and looking at other users’ solutions on Kaggle and comparing them to my own.
6)Are there any specific requirements such as department, CGPA, or other criteria for this position? Additionally, do certain PORs or EAAs enhance one’s chances of securing this internship?
Fidelity opens for dual degree students of all the departments with a CGPA of more than 7.5 but having a CGPA of more than 8 and being from a circuital department certainly gives you an edge. PORs and EAAs are not very important, but they can become a good point to talk about during your HR interview.
7)According to you, who should ideally apply for this job?
Anyone who is interested in AI research with an interest in finance would be an ideal candidate for this role. This will give you an upper hand if you want to switch to other asset management firms like Blackrock, Vanguard or even financial service firms like Capital One and Slice.
8)What are some of the major points you think would be valid to mention in your CV while targeting this profile?
You must try to add as much points as possible from the following as the company does not take a coding test, so making an impressive CV becomes extremely important.
2. Projects and Internships in NLP must be mentioned as the company works with these a lot.
3. Financial data analysis related projects and LLM projects will give you an upper hand in the CV shortlisting.
9)Lastly, what advice would you like to give to the students aiming to grab CDC internships this year?
The CDC internship process is very tolling on the mind and body with tests so don’t give up even if you don’t get a day one or day two offer or even shortlisted. Keep trust in your preparation and skills. You will definitely get a chance to show them, and when you do, make sure you make it count. Make sure you prepare for interviews by taking mock interviews and get your CVs evaluated by seniors in the domain you wish to pursue. I wish all the best to all the people sitting for internships this year. Believe in yourselves, and you can do it.