Isaac: My Data Analyst Career Journey

Alex: Thank you for taking the time out Isaac for this interview with DataAnalyst.Com. I’m looking forward to this!

Isaac: Of course! I’m looking forward to it as well. I have a lot of passion for analytics and I’m looking forward to sharing that with you and your audience.

Great, so to start us off can you please introduce yourself to our site’s readers out there?

Yes, my name is Isaac D. Tucker-Rasbury and I am a data analytics professional with a little over a half-decade of working experience.

I did not go to school for “analytics”, but rather double majored in “economics” and “africana studies”. The most formal schooling I have in data is earning a Data Analytics certificate from the University of California Berkeley.

After graduating college in 2018, I worked in various industries over the next six years including operations, financial planning and analysis, financial technology tutoring, consulting, entertainment, compensation, and most recently government and healthcare. In total, I’ve held six full-time roles, three volunteer positions, and one part-time job all between 2018 and 2024. Of all the places I’ve worked, people tend to like to hear about my time at Goldman Sachs (financial services), Slalom (consulting), and Netflix (streaming and entertainment).

Those experiences and the backing of my supportive wife and family brought me to where I am today.

I’m currently working remotely full time as Senior Data Analyst I on the Civic Tech team at BlueLabs - we help our government/public sector clients change behavior and drive radically better results for the United States public.

That’s me in a nutshell professionally.

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

My journey into data analytics began from a place of curiosity and a need to distinguish myself early in my career, particularly during my time at Goldman Sachs. Initially, my drive stemmed from a desire to compete with my colleagues and to become indispensable. Despite facing obstacles, such as missing a firm-sponsored data analytics boot camp due to my team’s obligations, my resolve didn't waver. This determination led me to try to teach myself SQL, marking the beginning of my path in data analytics. That was way way back in 2018 through 2020.

My first full-time “data analyst” role wouldn’t be until October 2021. That was with Slalom on their “Financial Planning and Analysis” (FP&A) team. Slalom is a global consulting firm focused on strategy, technology, and business transformation. The FP&A team I worked on analyzes disparate datasets to surface insights to C-suite and regional leadership by conducting market research. Our work answered 3 strategic questions: 1. Who can we do business with? 2. Where are our prospective clients? 3. How much business can we do with each client in each place? We used a lot of Excel, SQL, Microsoft Power BI, a sprinkle of Python, and a lot of research muscles.

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

This answer has changed for me over the years, but most recently what I find most exciting about being a data analyst is that I can use my skills for social good.

I work full-time with an analytics consulting contractor, BlueLabs, on the Civic Tech Team to improve the systems behind Medicare, a federal healthcare program. In my personal time, I volunteer for a tech talent coordinating non-profit, Bluebonnet Data, which supports socially and politically progressive U.S.-based campaigns and non-profits. In my past life, I volunteered for a men’s mental health non-profit where I analyzed social media data to identify the organization’s audience to help with brainstorming audience engagement tactics. And, at a different point, I volunteered for a non-partisan civic-tech startup intent on educating voters and helping Americans find like-minded candidates and interest groups without injecting partisanship.

I did all that in the last three years and have loved just about every moment of it. I wouldn’t have been able to do any of that without getting into this world of analytics.

In your current senior data analyst role, you’re working in the consulting sector for a “Civic Tech” team at an analytics contractor, if I understand correctly. Could you tell us a bit more about what your day-to-day looks like, and share how what you do drives insights and business decisions? How are you using data in your role, and what is the impact you’re able to achieve?

That’s a big question, but I think we can answer it in parts.

So, what I do is I work on the Civic Tech team at BlueLabs, and like I described before our team helps government/public sector clients change behavior and drive better results for the services administered for the benefit of the United States public. The overarching project I am working on is related to Medicare. Medicare is federal health insurance for anyone age 65 and older, and some people under 65 with certain disabilities or conditions serving tens of millions of Americans.

My days on the project fluctuate between a lot of meetings and a lot of solo time to work on my assignments. That said, every day starts with a stand-up. We work using the agile method, which means we get on the same page in a “stand-up”, sync up with anyone we need help from, and then we’re off to solo work and or meetings. Tasks are assigned roughly a week and a half, maybe two weeks out at a time.

When it comes to the actual work, I am working on two teams simultaneously. On the first team, I am helping create a data pipeline using SQL, dbt, Visual Studio Code, and GitHub/Git to replace the government’s legacy infrastructure and in the process improve the flow of information. The second team is “Outreach”. I started with them recently and am writing SQL queries to create summary reports for an external stakeholder.

When it comes to the impact I have, I feel good about being able to say without exaggeration that I help millions of people get better healthcare information.

That was a mouthful, but that’s my work and I love it. I log in every day happy about what I’m adding to the team and, to be a little cliche, the country.

How did you start improving your skillset as a data analyst? What are you currently doing to keep up with the ever-changing data analytics industry?

Because of my grandfather and mom, I have always thought of growth as an iterative process. Analytics has been no different. When I realized that I wanted to be a data analyst, I took in everything I could. I tried listening to podcasts, following tech blogs or newsletters, reading documentation notes for tools of interest, watched Youtubers, and identified professionals online who share solid advice on current events in the analytics and adjacent industries. Second to that, I read up on my industry domain-specific knowledge. When I was in finance, I studied up on the financial products my team managed. When I was in compensation, I took a course (paid for by my company) to learn the “fundamentals of compensation philosophy”. I did this all over and over again until I built a small library of knowledge for myself to draw from.

Now that I’m in the analytics industry, I’m a little less entrepreneurial and a little more discerning. I learn what I need for work and volunteering, and what I need for my next career move. That process of shedding what isn’t relevant means I can go deeper into subjects I care about. Second to that, creating analytics content online for the last year and change has also helped me by fostering a community of like-minded professionals to act as a sounding board for the ideas I’m mulling over. I enjoy sharing ideas with others; it brings the work to life for me and that helps me want to keep my skills sharp.

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

The growth I’m eyeing right now…there are two sides to that answer - on the job and off the job. Off the job, I am interested in earning a certificate and/or master's in data science with a concentration in political science. I’ve previously said that there was no need for that, but I may have to eat my words. On the job, I am leaning into stretch projects to expand my skills in data pipelines and analytics engineering.

Something that a lot of people are wondering and asking about - What recommendations would you give to someone who is looking to join the data industry and get their first full-time data analyst position?

This takes me back to my beginnings. A few months after I landed my first data analyst job, I wrote this sprawling article to commemorate everything I’d done to land that job. Here are the 6 tips I boiled the process down to:

1. Develop a firm grasp on the basic tools (ex. MS Excel & Power Query, SQL, DataViz (Power BI or Tableau), and Python)

2. Create a public facing portfolio (ex. Projects, writing, videos, social media, it just has to work for you to consistently share)

3. Share your work publicly on LinkedIn and other social media

4. Write a solid resume, submit applications and get to networking ASAP

5. Develop a habit of lifelong self-study

6. Iterate on this to make it your own

Anything you'd like to highlight, or add? Something that not specified above but you hear a lot? Or would be helpful for people to know?

Allow your interests and convictions to lead you in deciding what to work on. Let’s assume you are capable enough to work anywhere and on anything. Then the next question is, “what do you want to work on?” If you pick something that fills your metaphorical cup everyday, you will benefit from the natural momentum of your interests. Pick something exclusively for clout or pay, and that will get old quickly. I’m fortunate enough to have been able to follow my interests and now even my convictions. I wish you out there reading this a fulfilling, and then yes a well paid, career.

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?

Isaac: I am using AI tools to:

1. create the skeleton of prospective SQL and DBT queries,

2. identify issues with syntax, and

3. explain the logic behind code in plain terms.

I see these tools being to analytics professionals what a hammer is to a construction worker, one of many tools necessary to efficiently work through problems.

It’s not a replacement for having a personal analytics muscle though. The industry expertise and the real people out there on the other end of what we build still need to get our help at the end of the day. The work isn’t done until we’ve built tools and systems that do that well. AI tools are a long way off from being able to build those tools for us…for now.

Thank you so much, Isaac. How can people find you out there?

People can find me primarily on LinkedIn and Medium, search “Isaac Tucker-Rasbury”.

I am also on Youtube at “Data Analytics with ITR”.

My personal homepage is here - https://bio.site/ITR

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