My journey
Computers and programming come naturally to many of us, as do the rigors of math and statistics. For many of us, this inclination towards the wonderful world of coding and numbers has been a crucial part of our lives – having studied these subjects from an early age, many of us continue the practice and end up find themselves in well-paying jobs and respected positions as computer engineers, data scientists, data engineers, et al.
I was not one of those few. My date with computer science and math ended when I was 15 – or so I thought. My undergraduate degree was in international relations and international business, and after that I worked in business development.
I tell you this to establish my lack of technical credentials (beyond serious curiosity and initial elementary exploration of the world of data science) before enrolling in the MS-Applied Data Science course at iSchool, Syracuse University, and to reinforce that you don’t need to have a storied past with computers and data, or incredible knowledge of complex algorithms to land a technical and rewarding internship .
Reflecting on my internship experience, here are some of the most important takeaways from the internship application process, interviews, and my ten weeks of work as an Intelligent Process Automation Engineer at Chubb.
Apps
Working with iSchool Career Services early allowed me to have my resume and resume ready. Also, talking with their counselors helped me understand how to approach the job search; from identifying my skills and desire to add technical knowledge to my portfolio to developing an action plan to approach recruiters and companies; talking with said advisors helped create the platform on which my internship search was based.
An important point to remember here is that rejection is part of the process; Changing your mindset about rejected applications from one of unhappiness or desperation to one of learning – understanding why you may have failed and how you can improve is vital. Career Services gave me incredible support here, and their counselors were always on hand to make sure I never felt too bad about job rejections.
Interviews
Depending on the company and the position you are applying for, you may have code tests, online assessments, and live interviews. The specifics of the process are changeable and differ.
My interview experience lasted two rounds with no online assessment or live coding. My first round was a candid conversation with HR. This was followed by a longer tour (around 1.5 hours) which saw me interact with my team lead and the CIO for Intelligent Process Automation at Chubb.
The interview took me through my final project for Applied Machine Learning and explaining the ML algorithms used and why these algorithms, in particular, were used. I’ve been asked about the assumptions that different algorithms make; there was also a series of questions designed to help my interviewers understand how I solve problems, how I interact with teams, and how I might work in Chubb’s techno-cultural environment.
Confidence and ease of communication were key to my interviews; I knew my CV inside out, I knew my project work and the research that underpinned the things I had done, and most importantly, I was happy to communicate my ideas through conversation and not monologue; fostering a discussion with my interviewers helped me establish a professional counseling and mentoring relationship that continues even now that my internship is over.
Internship at Chubb
My internship allowed me to work as an intelligent process automation engineer at Chubb, the world’s largest P&C insurer; the internship lasted ten weeks – from 2n/a week of June until the end of August and had me work at Chubb’s office in Jersey City.
The first two weeks at Chubb focused on using their WorkFusion software and earning a plethora of certifications. During that time, I attended countless hours of certification-focused tutorials and assignments for machine learning, data science, and the WorkFusion platform. Additionally, the first few weeks also kept me busy with a multitude of activities aimed at helping students assimilate into Chubb’s culture and get to know the team I would be working with.
From week 3 of my internship, I was assigned to an email classification and routing automation project. In short, we took business rules from subject matter experts in the business operations team and used them to classify emails. These classified emails were then sent to the appropriate team at the appropriate insurance stage (agency, brokerage, legal, claims, etc.). Initially, I used Python to create a simple rule-based classifier; news stories based on this classifier were assembled and presented as Excel spreadsheets. Over time, we realized that a minimal subset of mails (<50%) could be effectively classified based on said rules.
This realization inspired my internship project, which I worked on from week 5 to the end. Realizing that business rules were difficult to grasp while not being as efficient as expected, I worked with a fellow intern to develop an ML-based classification system; however, we had to implement code for identifying, cleaning, processing, and storing data.
Since I was working with real world emails and a number of those emails contained attachments, I first had to extract the text of the email and identify if the email contained any attachments and the type of attachments of said mail. When the attachment was a pdf, I also had to figure out if the pdf was searchable, and if not, implement OCR (we used PyTesseract for this). Essentially, this internship had me working with unstructured data, which I then struggled to cleanse and process. Once the data was in a usable state (text only), I passed it through many algorithms before using a Random Forest based classifier. This, in turn, increased email classification efficiency from 40 to 80! »
Reflection on my internship
Working at Chubb, in addition to giving me confidence in my ability to work with computers and data and to write effective code to deal with the problems we encounter in data, has also helped me acclimate to the work environment in the United States. I learned how to deal with problems not only by trying to find solutions on my own, but also through collaborative communication. most importantly, working at Chubb has allowed me to learn from courses such as business analytics, data analysis and decision making, applied machine learning and quantitative reasoning for data science and to use them to solve real-world problems.
In fact, my Applied Machine Learning course gave me most of the tools I would need to work with data at Chubb! Everything was covered in class, from data processing and cleaning, transformations and PCA, to applying ML algorithms and selecting the best model. Other business analytics and data analysis and decision making helped me working with Excel – it also allowed me to work with teams that weren’t mine just to show them how they could optimize their use of Excel using tools such as pivot tables, for example. Finally, quantitative reasoning for data science was integral to my ability to make sense of statistics, fit models, and ensure data was presented in a format our algorithm could work with.
Tips for finding an internship
- Prepare your curriculum vitae, CV and cover letter as soon as possible. Meet career services early and meet them often.
- Identify areas of interest and research internships in those areas, focus on what you can learn and how the internship in question can/will help you gain the insight and experience you seek
- Rejections are part of the process. Accept them as learning experiences; use the feedback you get from each rejection to grow as a student and as a potential professional.
- Apply early, apply often, apply a lot, and focus on your applications. You have very little to lose by applying and a lot to lose by not applying.
- Tailor your CV to the specific role you are applying for; not all positions have the same requirements; make sure your resume meets job requirements where you can.
- Trust what you know but accept when you don’t know something. Accepting your limitations and identifying how you can overcome those limitations is better for you than being terribly wrong.
- Review your CV and make sure you know what’s on said document before your interview – it’s not entirely necessary. Still, I’ve always found it to be an easy way to build confidence in an interview.
- Provide a conversational environment – although an interview is a formal setting, there is no reason it should be uncomfortable for any of the parties involved. Treating it like a technical conversation takes a lot of the pressure off your shoulders, making the interview much easier to get through.
- Networking is vital; networks won’t just help you secure professional roles. People in your network can be sources of information to help you solve seemingly complex problems quickly. Your manager, your colleagues and the company you are interning at want you to grow – they want you to succeed. Remember this and use the available resources to grow.
- Trust what you know and support yourself to learn what you don’t know. One of the most amazing human skills is our ability to learn not only from ourselves but also from others – using the internet, talking to your bosses, interacting with your colleagues and seizing every opportunity that comes your way. to improve.
- Take time. It’s extremely important to learn and grow, but you also need time to rest and recuperate – don’t skimp on that.
Enjoy. You always learn more when you can have fun – attend workplace events. Chubb, for example, has organized a great tech expo and regular climbing sessions around town. Find events you love wherever you are and attend!
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