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In today’s writtencast, I am joined by Christina Stathopoulos, a former Analytical Lead at Google and now independent consultant. She is also a LinkedIn Learning Instructor, a part-time Academic Director and Professor, and an international speaker. In this episode, we explore her journey in analytics and speaking.
Thanks so much, Christina, for gracing the writtencast today. Let’s start with your journey. How did you get into data analytics?
I have been fascinated with numbers from a young age - math and statistics were some of my favorite classes growing up. This drove me to eventually pursue an engineering degree, which I later dropped for a statistics-related degree, bringing me back to my love for pure numbers. Although it has been a ‘bumpy’ road along the way, I always stayed true to my love for statistics, and it only made sense to pursue a career in the data domain. I have dabbled in all 3 of the core tracks: data analytics, data science, and data engineering.
What’s the origin of the Data Whisperer name?
A Whisperer is a person who can tame or control animals. I do the same thing with data: taming the data and then acting as a bridge between it and the business. My goal is to help companies unleash the power behind their data. I advocate for more data-informed processes and a data-driven culture.
Tell us a little about your work at Waze
I was working at Waze for the last 2 years, preceded by over 3 years working for core Google. Within Waze, I led analytical studies and strategy across several advertising verticals for North America. I supported our Sales team, thus monetization of the Waze app, by bridging the gap between our data and the business. I focused on finding unique ways to use our 1st-party data, sometimes mixed with 3rd-party data and client data, to drive strategic decision-making around advertising, strategy, and more. My day-to-day involved a lot of SQL (classic and geospatial via S2), data visualization (classic and geospatial), project management, stakeholder management, and data storytelling.
You recently left Google (and Waze) after over 5 years. Why did you stay so long, why did you decide to leave, and what is your view on switching roles too often as far as career progression is concerned?
Google is where I honed in on developing strong skills in analytics, communication, and project management. I stayed for over 5 years because it kept me on my toes and was a fascinating place to work, particularly if you want to be close to advancements in the data space. I also particularly enjoyed the latest work I was doing when I changed roles to work for Waze almost 2 years ago and was thrown into the fascinating world of geospatial data.
Ultimately, though, I think that staying in the same place for too long in today's work environment is more detrimental to your career progression than beneficial. There are a select few wherein staying in the same place can benefit them as they rise in the ranks from their early days. Still, I firmly believe that job-hopping is more strategic in most cases and will create much more accelerated professional growth.
The ideal window is 2-3 years per company and negotiating a higher position, higher responsibilities, and higher pay with each move. I left Google because I felt like it was past time for me to move on and try something new, to accelerate both my professional growth and continuous learning journey. I also have a few personal projects to pursue. I want to make them happen in 2023, so stay tuned :)
What do you know now after working with data for five years that you wish you had known when starting?
That there is a certain degree of messiness involved in working with data that you can never resolve. I am a perfectionist, so I had to learn to accept that things will never be 100%, and in a related sense, the 80-20 rule applies well in most cases.
As an Analytical Lead, what does your tech stack look like?
I principally stuck to the Google ecosystem: BigQuery for storage, data manipulation, and querying, Looker Studio for automated reporting, Google Sheets for quick data visualization or exploratory analysis outside of what I did with SQL. I also used CARTO for more advanced visualization of geospatial data.
What are the top three skills desired when hiring a data analyst or data scientist?
SQL, Statistics, and Communication.
I think on the hard skills side, everyone seeking these types of roles needs to have a solid command of SQL and a good understanding of statistics. From there, hard skills will differ depending on the role and company, so one can specialize in all sorts of programming languages and tools for analysis, modeling, and visualization. On the soft skills side, communicating effectively is invaluable and will make any candidate stand out in the recruitment process.
How does your role as Analytical Lead differ from an individual data analyst contributor role?
Before Google, I worked as a data engineer, so I must forewarn you that I have never held a data analyst role in the traditional sense. Upon joining Google, I held several Data Specialist roles, most recently as an Analytical Lead at Waze. In contrast to what I have learned other data analysts do regularly, the Analytical Lead role is very independent and requires full project management. Data projects are led and fully executed in an independent setting, bringing in dedicated data scientists or data engineers when the project reaches certain levels of complexity (but still being managed by the Analytical Lead).
The Analytical Lead role also acts as a ‘data translator’: building a bridge and communicating between the sales or business teams and the data or tech teams. This is a unique position to be in that requires business domain knowledge, stakeholder management, and technical skills to succeed. It is a cross-functional role and sits right in the middle of many different teams.
What role has being a data science facilitator played in your role as an Analytical Lead?
During part of my time at Google and Waze, I took on a 20% project where I facilitated an internal data science course. Education has always sat close to my heart, and I enjoy teaching others. It is a very rewarding activity to see the change you can inspire in others and the passion you can ignite in them for a subject like data. I taught Google analysts and engineers around the globe how to better apply statistical theories to data to solve business problems. My involvement in this project contributed to my full-time role because it gave me a way to flex my communication skills by putting them into practice, learning how to explain complex topics and break them down into understandable pieces while at the same time, learning more about statistical techniques myself along the way.
*For those unfamiliar with the term ‘20% project’, the concept that Google started many years ago allows employees to take on an additional project or initiative outside of their core role and spend 20% of their time dedicated to working on it. It is supposed to empower creativity and innovation.
Which are your three top books for 2022?
This is always a tough question for me because I read a lot of books throughout the year! Some of the top books I read in 2022, split by common genres…
Novel: A Man Called Ove by Fredrik Backman - A uniquely written story about an equally grumpy yet loveable old man with a big heart.
Sci-fi: The Ministry for the Future by Kim Stanley Robinson - Climate change science fiction that feels disturbingly real, covering the story of a governmental body called The Ministry for the Future that sets out to reverse the human-led damage done on Earth and move toward more sustainable living.
Non-fiction: Spillover by David Quammen - A monster of a read, medical non-fiction that covers zoonosis (animal infections transmissible to humans) and is extremely helpful in understanding the phenomena that causes something like the Covid-19 pandemic.
And if I may add just one more book, a data-related book, because I think this audience will be very keen to hear. One of my favorites from 2022 was Be Data Literate by Jordan Morrow. This was one of the first books I read to kick off the year, and it does a great job of breaking down data literacy topics that everyone should be familiar with. His second book recently launched too: Be Data Driven!
What has been your key observation from traveling to 10+ countries to speak? (and traveling through over 50 countries for leisure!)
I have learned, sometimes the hard way, that the way you communicate must adapt to the culture. I realized that this is a larger reflection of what needs to be done within a company: adapting how you communicate to each team. This all reinforces how important it is for you to understand your audience whenever you want to communicate a message and have it resonate, regardless of whether you are in an informal or formal professional setting.
How has being bilingual helped you advance your career?
I learned Spanish as an adult, starting from scratch around 22, and it continues to be a constant learning process. Being bilingual has opened many professional doors for me, considering that I speak two of the most spoken languages in the world: English (native) and Spanish. I also recently relocated to Spain, and speaking these two languages here is the strongest combo for a successful career in the business world. It allows me to establish trust across various cultures on a team, and my work possibilities practically double if I can perform the work in both languages.
You have authored several publications. How important is writing as a skill in advancing a career in tech?
I am more of a reader than a writer (hence my #bookaweekchallenge, which we can discuss later!). I have to make an extra effort to write because it does not come naturally to me. Thus, I only do so occasionally. Whether writing proper publications or producing short-form content (I personally do more of the latter), it is important to use these mediums to get your voice heard. This helps establish thought leadership and trust within the tech world, which can ultimately open more doors for you professionally.
Tell us a little about your LinkedIn journey. How did you get started, and at what point did you decide to double down on the platform?
I started being active many years ago, so building a solid network on LinkedIn did not happen overnight. It originally started as a part of my job search effort when I was completing my Masters back in 2016. In the last two years, though, I have truly doubled down on using the platform to build my brand and establish a voice within the international data community. I enjoy being able to help others in their data journey while also networking and building connections with other fantastic professionals in the data space. I also use the platform to stay up to date with the latest, following and interacting with leaders in my field.
What inspired the weekly book recommendations? How do you make the time to go through all those books?
It started as a personal goal that grew into a community effort. It is meant to foster positive habits and a continuous learning mindset. I host the #bookaweekchallenge and #bookamonthchallenge on LinkedIn to encourage others to pick up a book and join along. For me, it’s a healthy way to disconnect from electronics (I only read paperbacks), and it keeps me in a continuous habit of learning and growth. I constantly change what types of books I am reading, which helps keep me on my toes. They never fail to amaze me. Even novels or science fiction have great lessons to be learned. Making time for it is a matter of creating healthy habits. I have consciously substituted excessive time on electronics (watching series on the TV, scrolling through Facebook) and replaced it with more time spent reading books.
I am a Google Developer Expert in Machine learning, not a Google employee. People often ask me how to get a job at Google, and unfortunately, I can’t help them because I don’t work there. Got any tips for them?
I get asked this all the time; unfortunately, there is no secret formula. You can use it as a professional North Star but remember there are many wonderful companies and teams outside of Google. The road doesn’t end just because you have not landed your dream job at Google.
To get into Google or any of the top-desired MAANG companies, first define a clear career path for yourself. For example, within the data world, which of the 3 core tracks are you focusing on: data analytics, data science, or data engineering? Build up strong experience and show a clear impact within your domain.
In parallel, find a way to stand out from all other candidates within your field. You can do this through various side projects: build a personal brand, launch a podcast or YouTube channel, do volunteer work, etc. It is a bonus if you can build a direct connection between your side project and your data career, a bonus that can ultimately attract the eye of hiring managers and make them eager to learn more about you and what drives you.
What’s your view on the new era of generative AI. Do you think it will take over all creative jobs?
I am fascinated by the new era of generative AI and have been following it closely! We have seen developments in AI take a large leap forward with prompt-to-text, pictures, video, music, and more. The public release of this technology is still very new, and we can only prospect on what may happen next, but I am sure that 2023 will be an exciting year.
Regarding generative AI taking over all creative jobs, I do not believe we are at risk of this yet. Creative professionals will have to adapt to this new technology creeping into their domain but will benefit if they learn to work alongside AI. Many professions can be amplified if adapted to work alongside machines. As the famous quote by Pedro Domingos goes, “It’s not man versus machine; it’s man with machine versus man without.”
I hope I am not proved wrong, but only time will tell. I am, on the other hand though, concerned with ethics and privacy as they relate to these advancements, given that regulation cannot keep pace with today's technology.
Where can people find you online?
My platform of choice is LinkedIn
You can also follow my LinkedIn Learning courses page here. I have only released one thus far but have new ones coming in 2023, so stay tuned!
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