https://ift.tt/SwpDqLN From Paralegal to Data Scientist — How I Started My Data Career Without a Quantitative Degree Sharing my tips and e...
From Paralegal to Data Scientist — How I Started My Data Career Without a Quantitative Degree
Sharing my tips and experience in landing my first data role within 1 year of completing a part-time data science boot camp
Why I’m writing this
I graduated with a Bachelor’s degree in International Relations and had only completed a handful of courses on statistics and economics. After 5 years of work experience, I started to pursue a career in analytics. I landed my first official data role within 1 year of completing a part-time data science boot camp while working full-time. I hope my experience and tips will be helpful and encouraging to others who aspire to pivot into the data science field.
My strategy was to work at the company that offered the most career growth potential.
I previously shared how I navigated my first career transition from working at a law firm to a start-up. I received multiple offers of varying roles, ranging from Customer Success to Legal. In the end, I accepted an offer as an in-house paralegal. It might seem counterintuitive why I chose the paralegal role when I was trying to move away from the legal field.
Because I wasn’t sure what I wanted to do next, I placed more weight on my career opportunities at the company rather than the title or the type of work I would be doing. After ongoing career conversations with my manager, I expressed interest in trying a different role within the company. With her support, I made a role change to the Customer Experience (CX) team.
In the new CX role, I gravitated towards data analytics work and identified all the possible resources to speed up my learning.
Three distinct experiences stood out and allowed me to have applicable job experience. More importantly, I was mentored by seasoned professionals through each of these experiences:
- I enrolled in a part-time Data Science course to learn foundational statistics and programming. This data science course was distinct as I was paired with a data science expert who was highly skilled in programming and ML techniques.
- I applied for and was accepted to a six-month fellowship with Delta Analytics, which provides pro-bono data consulting to nonprofits. I had the opportunity to apply what I learned in the boot camp and network with other data professionals.
- I partnered with my manager and the data analytics lead to craft a custom rotation program where I would work closely with the Data Analytics team. During the rotation, I created a data product that was useful for the CX team and the entire company. I also received mentorship from the managers and team members and got a really good sense of what it’s like to work on a centralized data team.
After completing the rotation, I began my job search to transition into a formal data role.
During my job search, I experienced many rejections because I failed to provide structured responses to pass case study interviews.
Initially, I applied for many types of data roles within different domains and departments. Some were on the business operations team focused on financial metrics, others were product roles that analyzed user behavior and funnel metrics.
With such varying roles and domain areas, it was overwhelming to prepare for case studies and complete take-home challenges. I would spend hours trying to learn about different metrics and product areas I was not familiar with.
Despite my best effort, I would not advance much further than the first round because I would fail miserably on the case study interviews. Worse than failing, it was hard to know how to prepare for future interviews because I felt so overwhelmed by how much I didn’t know. I took time to reflect on how to move forward and realized I could apply for roles that highlighted my strengths instead of emphasizing my weaknesses.
To increase my success rate in interviews, I focused on positions where my domain knowledge allowed me to provide structured approaches to case studies and take-home challenges.
After numerous failed interviews, I narrowed down the data roles I applied to just those within the Customer Experience and Operations space. By doing so, I could focus my interview preparation and learn from each round at different companies — whether it went well or not. I landed a new job within 2 months and my domain knowledge allowed me to hit the ground running. I knew what questions to ask business partners and had my first win within a few weeks despite it being my first formal data role.
Summary of tips for those currently employed, but not in an official data role:
- Partner with your manager to find data opportunities at work or design/apply for a rotation program. Personally, this was the most critical and impactful experience in jump-starting my analytics career. If you are already at a tech company, ask your manager if you can have dedicated time to work on data projects and receive mentorship from a data professional. This was possible for me while at a Series D startup with a size of ~500 employees. This goes back to my earlier point about deciding to work at a high-growth startup — even though there wasn’t a formal rotation program in place, my manager and I were able to quickly partner with the data analytics leader and define the requirements and timeline of the rotation within a few short weeks. If you are at a larger company, you can propose the rotation program to your manager or directly apply for the rotation if this is offered. This is also a good way to get a feel for the work before fully committing if you are unsure. I’ve met young professionals who did some data work in their roles and ultimately decided to stay in their operational roles.
- Complete a data science course to learn the technical skills and foundational concepts and build credibility. This might be cliche, but it’s the fastest way to learn technical skills and grow your knowledge rather than to wait for the right project at work or the perfect opportunity to change your job function. Waiting for such opportunities will take much longer than a dedicated time investment. By completing a boot camp, you not only have a portfolio of real projects to demonstrate your skills, but it can also get your manager’s support in your career change. It can give them more confidence to look for and assign data projects to you because you have demonstrated your capabilities.
Additional tips for job seekers recruiting for their first data role:
- Be open to job titles when job searching. Even if you completed a data science course, a product or data analyst role could offer similar career opportunities. You should be able to get a sense of how technical the role is during the interview process and if it is a good fit for your skills. I’ve met successful career changers who landed a job relatively quickly after their boot camp that were open to different job titles. Separately, you never know what will happen to a role after you join the company. Many companies have reorganized their data teams from a decentralized to centralized model or vice versa, and changed job titles as part of the rebranding.
- Leverage your past experience. You likely have valuable domain knowledge that others in a technical role may not have. If you worked at a bank, you probably have a deep understanding of how customers behave with their accounts or create risk to the business — use it to your advantage. Data roles within a Business Operations or Finance team could be a good fit. If your background is in customer support, you can look for data roles related to customer service and agent performance metrics.
- Look for volunteer opportunities to learn from other data professionals and work on real data problems, such as Delta Analytics. I found this more helpful than working on Kaggle projects independently because I needed accountability.
Conclusion
I hope this article offers you encouragement and insight on navigating a career change into a technical role from non-traditional backgrounds. Remember — landing the job is only the start of your data career journey, but the growth and learning mindset you had when preparing for the journey should always apply as you deepen your knowledge and experience!
From Paralegal to Data Scientist — How I Started My Data Career Without a Quantitative Degree was originally published in Towards Data Science on Medium, where people are continuing the conversation by highlighting and responding to this story.
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