Christine: My Data Analyst Career Journey

Christine: My Data Analyst Career Journey

Today, we're bringing you an interview with Christine - she's the former Director of Data at Vimeo, founder of the Analytics Accelerator

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Hi Christine, thank you so much for taking the time. Please introduce yourself to our site’s readers.

Hello hello! I’m Christine - I’ve worked in analytics since 2015, starting out in consulting, then working as a data analyst, data scientist, bootcamp instructor, and eventually becoming a data director at Vimeo. Last year I started my own bootcamp and mentorship program with the mission of equipping people with the real hands-on skills, analytical thinking, and business frameworks used on the job - so that they could land their first data job and find the same kind of professional growth, opportunities, and confidence in their careers. I’m normally based in NYC but I travel to Paris often for creative projects in fashion and dance photography. Outside of work I’m into running, meditation, house / techno music, and meeting aspiring analysts and creatives from around the world.

Can you share with us how you entered the data analytics industry, and tell us about your first data analyst role?

I was actually trying to transition out of another industry when I landed in analytics - I had been working towards being an actuary, which requires taking extremely rigorous exams over the course of 5-10 years. I felt the exams and the industry had little room for creative thinking and innovation - and while working my first actuarial job, I happened to sit next to data scientists, whose conversations I could overhear. Their projects intrigued and motivated me enough to work towards making the switch - so over the course of a year I studied the technical skills on my own and transferred internally while working at Deloitte, from the actuarial team to the advanced analytics team in 2015.  

What is it that you're personally finding most exciting about being a data analyst?

There is so much room for creativity and curiosity in data analytics. Once you reach the layer of analytics beyond reporting and dashboard building, the job itself is the art and science of asking “why”:

“Why is this metric important? Why did it fluctuate? Why does the data look this way, and what can we do about it? How can we slice it to understand what’s going on underneath?”

There are many layers of thinking and even social skill required to be a strong data analyst - like negotiation (getting buy-in from stakeholders), system-based thinking (in architecting data pipelines), adaptable communication (in verbally and visually presenting insights), and of course, the logical and technical fun (and challenges) that come with working with code.

To a certain degree, this flexibility and ability to grow these skills depends on the company, the team you’re working on, and the industry, but when those elements align well with your goals, being an analyst is a really fun practice of bridging the quantitative with the qualitative in order to understand why things are the way they are.

Throughout your career, what did you learn about using data insights to make an impact in these various organisations and industries? What would you say all your roles had in-common - i.e core, and on the other hand, did you have an experience where you really had to get outside the box and the usual path?

One of the most important skills I acquired was system-based thinking: as in, being able to think about any situation in varying levels of abstraction, and adapt accordingly. As data analysts, our work is only as good as our ability to communicate - which requires a keen understanding of which “level” of the organization you’re working with anytime you want to deliver insights in a way that actually makes an impact.

As an example, a simple analogy: think about a user-level table, with another table rolled up to the daily level, and another table rolled up to the monthly level. To other data analysts, I can talk about the user-level table. To team managers, I can talk about the daily level. To leadership, I speak on the monthly level. I call this “degrees of detail” - in every project, in every meeting, I consider which degree of detail I should be speaking at, which enables the audience to actually understand and care about these insights because these insights are directly related to their goals and concepts they understand. This is a skill that I see strong data analysts develop over time, and it translates across all industries and organizations.

What are you currently doing to keep up with the ever changing data analytics industry?

My pulse on the industry is through two ends of the spectrum - through students and mentees who are applying to early-career data analyst roles who tell me about their interviews and subsequently what hiring managers are looking for, and through colleagues (other data analysts, data directors, hiring managers, consultants) who keep me in the loop on tools, challenges, and business questions. While the tools and technology may seem to evolve quickly on the surface, I believe the underlying skills required to wield those tools effectively are slower to change: critical thinking, an ability to persevere with the question of “why” something is happening, and a combined curiosity and adaptability to learn these new tools as they arise.

What is your vision of what you'd like your next career growth to look like?

Over the next year my goal is to see 100 more aspiring analysts and career transitioners over the finish line to a new, fulfilling career in data!

Speaking of career growth, since you started your own coaching business, can you share what prompted you to start helping others grow? What are some of the key things you focus on?

It’s been a combination of three forces:

1) personal experiences in which I witnessed how much someone’s life path can transform through having technical skills that elevate their professional opportunities,

2) seeing a lack of resources that teach the thinking and mindset behind being a data analyst, not just the tools, and

3) a love for building communities and seeing people gain confidence through learning new ideas.

I’m sure this is something that a lot of people are wondering and asking you about in your Analytics Accelerator - What recommendations would you give to someone who is looking to join the data industry and get their first full-time data analyst position?

As soon as you have foundational technical skills, you need to apply these technical skills to real business problems as much as possible - not focus on getting to higher levels of difficulty on Leetcode. With how competitive the market is right now, my advice is to think creatively about how you can create opportunities for yourself to apply these skills, instead of blindly applying to jobs that are saturated with other data analysts. This includes using your personal and secondary network to do volunteer analytics work, or freelance analytics work - for example, even helping an Etsy shop owner understand her store trends and customers in Excel - to gain experience in which you use real data to help real people.

This will improve your resume, give you experience to talk about in interviews, and equip you with experience that is relevant to the actual job much more than racking up points on Kaggle.

An extra one: How do you see the increased availability of AI tools such as ChatGPT, Bard etc, impacting the typical data analyst role? Are you using AI tools to augment your  thinking, analysis and overall work?

Historically, the data analyst role has leaned more technical skills-based than soft-skills based. With AI, this balance is changing - there’s less emphasis on being able to write code (AI tools can do this) and more emphasis on having strong communication skills, business domain knowledge of metrics and how they relate to company goals, and being able to negotiate and understand stakeholder needs in helping them make more strategic decisions, rather than focusing on reporting and dashboard building.

I’m really excited to see how these AI tools release analysts from the “lower-level” technical work and enable us to reach higher levels of  creative visualization, insights building, and strategic thinking.

This has been great, thank you again, Christine. Where could people connect with you?

My LinkedIn is here, where I’ll be posting tips and strategies for breaking into data based on my experience as a hiring manager. I’ll also be hosting free in-person and online workshops soon, also to be posted on LinkedIn. 

My mentorship program site is here.

And my photography is here, because why not!

Christine Jiang - Founder of the Analytics Accelerator
Christine Jiang - Founder of the Analytics Accelerator