My experience with data and machine learning began when I started the research data science master’s program at iSchool. I have established a foundation in ML through courses like Introduction to Data Science, Using Machine Learninga Fundamentals of data science. This provided the basis for everything I did during the internship. Of course, my project work for Applied Machine Learning is directly related to my internship landing, to begin with!
Computers and software come to many of us, as do math and numbers. For most of us, this interest in the wonderful world of coding and numbers is an important part of our lives – learning the subjects from a young age, many of us continue to work and earn ourselves a good salary. respected positions as computer scientist, data scientist, data engineer, et al.
I am not one of these few. I ended up experimenting with computer science and math at age 15 – or so I thought. My bachelor’s degree was in International Relations and International Business, and after this, I worked in Business Development.
I am telling you this to establish my lack of technical knowledge (beyond extensive research and some prior research in the world of data science) before enrolling in the MS course. -Applied Data Science at iSchool, Syracuse University, and focus on reality. It does not require an old job with computers and data, or an amazing knowledge of complex algorithms to secure a good and technical internship.
Reflecting on my work experience, here are some of the key takeaways from the internship application process, interviews, and my ten weeks working as an Intelligent Process Automation Engineer at Chubb.
Working with Career Services at the iSchool has already ensured that my resume and CV are ready. Also, talking to their advisors helped me understand how to approach job hunting; from realizing my skills and desire to add expertise to my portfolio to thinking of a plan of action to approach potential employers and organizations; Talking with mentors helped create the foundation upon which my internship search was based.
An important thing to remember here is that rejection is part of the process; change your mind about rejected applications from one of disaster or hopelessness to learning – understanding why you failed and how you can improve is important. Business services are very supportive here, and their advisors are always on hand to make sure I don’t feel too bad about turning down a request.
Depending on the firm and position you are applying for, you may have Code Tests, Online Assessments, and live interview rounds. Process details are subject to change and may vary.
My interview experience lasted two rounds without any web analytics or live coding. My first round was a direct conversation with HR. It was followed by a long round (1.5 or so) that saw me interact with my group manager and the CIO for Intelligent Process Automation at Chubb.
I went through an interview at my last project for Applied Machine Learning and explained the ML algorithms used and why those algorithms were used, in detail. I have been asked about the assumptions made by different algorithms; there are some questions designed to help my interviewers understand how I solve problems, how I interact with teams, and how I work culturally at Chubb.
Confidence and ease of communication are important in my interviews; I saw my continuity inside out, I saw my project work and research supporting what I did, and most importantly, I was happy to share my thoughts on of dialogue rather than monologue; Fostering a dialogue with my interviewees has helped me establish a professional relationship of mentoring and learning that continues even after my career is over.
Project at Chubb
My career saw me work as an Intelligent Process Automation Engineer at Chubb, the world’s largest P&C provider; The internship lasts ten weeks – from 2n.d week of June through the end of August and I worked out of Chubb’s Jersey City office.
The first two weeks at Chubb focused on using their WorkFusion software and earning a plethora of certifications. So far, I have sat through many hours of tutorials and workshops on machine learning certifications, data science, and the WorkFusion platform. Also, the first few weeks have seen me busy with a lot of work related to helping students get into the culture at Chubb and get to know the team I’ll be working with.
From week 3 of my previous training, I was assigned to work on the email account and routing automation program. In short, we’ve taken business rules from subject matter experts in the business community and used the rules to categorize emails. These emails are sent to the appropriate organization at the appropriate insurance level (business, brokerage, legal, claims, etc.). Initially, I used Python to create a simple rule-based scheduler; The report on this classifier was compiled and presented as an Excel spreadsheet. Over time, we found that only a small portion of emails (<50%) could be classified based on the rules.
This experience inspired my internship program, where I worked from week 5 to the end. After realizing that business rules are difficult to understand while not being as efficient as expected, I worked with a colleague to develop an ML scheduling system; however, we must implement codes for data access, cleaning, processing, and storage.
Since I am dealing with real emails, and since many of these emails contain attachments, I need to first extract the email and see if there are any attachments and what they are. link mentioned in the email. When the attachment is a pdf, I need to know if the pdf is searchable, and if not, then perform OCR (we used PyTesseract for this). Basically, I did this internship with unstructured data, and then I tried to clean it up and make it work. When the data was used (only the text), I ran through several algorithms before using a classifier based on Random Forest. This has increased the efficiency of the email address from the high 40s to the high 80s!’
Thinking about my Internship
Working at Chubb, in addition to giving me confidence in my ability to work with computers and data and write the right code to combat the problems we see in data , also helped me acclimate to the business environment in the USA. I learned how to solve problems not only by trying to find solutions myself but also through collaboration; Most importantly, working at Chubb allowed me to take lessons learned in courses such as Business Analytics, Data Analysis, and Decision Making, Applied Machine Learning, and Quantitative Reasoning for Data Science. and use them to solve the world’s problems.
In fact, my Applied Machine Learning course gave me most of the tools I needed to work with data at Chubb! Everything is done in class, from data and cleaning, transformation, and PCA, to using ML algorithms and choosing the best model. More business data and data analysis and decision making has helped me work with Excel – this has also seen me work with teams that are not mine to show them how they can improve in their Excel using tools like Pivot Tables, for example. Finally, Quantitative Reasoning for Data Science is critical to my ability to understand data, make valid models, and ensure that data is presented in a way that makes sense to the audience. Our algorithm works with.
Tips for Finding an Internship
- Get your resume, CV, and Cover Letter ready to go in no time. Meet professional services first and meet them often.
- Find interesting fields and find internships in those fields, see what you can learn and how the internship in question can help you gain knowledge and experience. you are looking for.
- Rejections are part of the job. Allow them to be learning experiences; use the feedback you get from each rejection to grow as a student and as a professional.
- Apply early, apply often, apply more, and watch your applications. You have very little to lose by applying and a lot to lose by not applying.
- Tailor your resume to the specific role you are applying for; not all situations are the same; Make sure your resume meets the needs of the job where you can.
- Trust your intuition but admit that you don’t know something. Accepting your limitations and knowing how you can work around those limitations will do you more good than great harm.
- Check your resume, and make sure you know what was said before your interview – this is not necessary. However, I always find it an easy way to increase confidence in an interview.
- Allow a conversation – even though an interview is a formal situation, there is no reason not to make one of the parties involved feel comfortable. Treating it as a technical interview will take a lot of pressure off your shoulders, making the interview easier.
- The internet is important; Websites don’t just help you secure business rights. The people in your network can be a source of information to help you solve complex problems quickly. Your boss, co-workers, and the company you’re in want you to grow – they want you to succeed. Remember that and use the resources at hand to grow.
- Trust what you know, and push yourself to learn what you don’t. One of the most amazing human skills is our ability to learn not only from ourselves but from others – use the internet, talk to your bosses, talk to your colleagues, and take all the time you can improve yourself.
- It takes time. Learning and growing is important, but you need time to rest and recover – don’t rush it.
Have fun. You’ll always learn while you can have fun – participate in workplace events. Chubb, for example, has a great tech show and regular climbing sessions in town. Find events that you enjoy wherever you live and participate in them!