The world of analytics is dynamic and full of opportunities. I recently read an article called Advancing Your Career Within Analytics by June Dershewitz, and it got me thinking about how difficult it can be to chart this and how some of my previous mentors got me to think about how to chart my career path.
It's not just about the next job. It's about building a fulfilling and impactful career centered around what gives you energy.
The Analyst Role as a Springboard
Most journeys in analytics start with an analyst role, whether it's as a Data Analyst, Business Analyst, Operations Analyst, or another specialized title. In these roles, you’ve likely mastered the fundamentals of tools like SQL, Excel, and visualization platforms like Tableau or Power BI. You have a solid understanding of data's power and its ability to solve business problems.
But where do you go from there?
I should acknowledge that you may be content being in an analyst role, and that’s totally okay. Analyst work is very rewarding for many people and you may wish to stay in a traditional analyst role long-term. If that’s your desire, use this article instead as a way of identifying some areas where you can grow within your analyst role.
Define What Gives you Energy, What Drains You
There are a few clear paths based on what you enjoy doing in your role. While I believe there’s no “test” you can take and get a simple result for what your next job should be, you can guide yourself just by simply determining whether you lean heavier towards the People, Process, or Technology portion of an organizational strategy.
My highly-technical 3-way Venn Diagram to describe PPT framework.
First, make a basic list of things you like and dislike about your current and past analytics roles. Then, organize the ones that you like into the PPT framework. It’s okay if they overlap multiple parts, but try to determine which way they mostly lean.
If you need help organizing them or getting started with questions, check out the list below.
People: Do you enjoy the stakeholder management portion of analytics work? Do you like to solve business challenges and build relationships across teams?
Process: Does the thought of working on a brand new strategy or redesigning a process from the ground up sound exciting? Do you enjoy creating or maintaining documentation?
Technology: Do you like digging deep into databases to find where data lives in a schema or table? Does a day full of writing queries sound like a dream to you?
What do you do with the drainers? I’ll cover that at the end.
Now, use the PPT category that you are getting the most energy from to narrow your paths as you move through the next sections.
Technology Path: Data Scientist or Data Engineer
“People” and “Process” is still important here, but this is a common aspiration for analysts who love the technical intricacies of data and want to delve deeper into advanced modeling or building data infrastructures.
Data Scientist:
Focus: Developing predictive models, using machine learning algorithms, statistical analysis, and communicating complex findings.
Skills to Develop: Advanced statistics, programming languages like Python and R, machine learning techniques, data mining, and strong data storytelling abilities.
Making the Transition: Consider formal education (Master's if you can get someone else to pay for it, or certifications), work on complex projects that involve predictive analytics to build your portfolio, and deepen your understanding of algorithms.
Data Engineer:
Focus: Designing, building, and maintaining the data infrastructure that allows data scientists and analysts to do their work. This includes data pipelines, warehousing, and ensuring data quality and accessibility.
Skills to Develop: Data engineering programming skills (Scala, Java), understanding of database technologies (SQL and NoSQL), ETL processes, pipeline tools (dbt, Airflow, prefect) cloud platforms (AWS, Azure, GCP), and big data technologies (Spark, Kafka, Hadoop).
Making the Transition: Certifications are valuable here, like Zach Wilson’s dataexpert.io bootcamp. Focus on understanding data architecture, learn relevant programming and platform skills, and look for opportunities to work on data infrastructure projects. You can build some pipelines of your own to build a portfolio and demonstrate competency.
People Path: Analytics Leadership
If you find yourself passionate about strategy, mentoring others, and driving the overall impact of analytics within an organization, the leadership path is the logical choice. Like the “Technology” path, other parts of the PPT framework will apply here, but this path is heavily “People” oriented.
Focus: Leading teams of analysts, setting the analytics strategy, stakeholder management, ensuring the delivery of impactful insights, and fostering a data-driven culture.
Skills to Develop: Strong communication and presentation skills, people management, strategic thinking, project management, business acumen, and the ability to translate technical insights into business value. Your EQ and AQ become particularly critical here.
Making the Transition: Seek opportunities to mentor junior analysts, lead projects, take initiative in strategic discussions, and demonstrate your ability to connect analytics to broader business objectives. Cultivating a strong network is also key, as discussed in my article "How to Cultivate a Network That Grows With You".
Process Path: The PMs
Analysts with a keen understanding of user needs, business strategy, and how data can drive product decisions are well-suited for a transition into product management.
Structured thinking, problem-solving abilities, and attention to detail developed as an analyst are highly transferable to project management roles, especially within data-centric environments.
I put these two together under the “Process” path because these roles are heavily focused on figuring out “How” stuff is done though require “People” and “Technology” like all of the other paths.
Figuring out which makes more sense for you will require digging a little deeper into each role below.
Product Manager:
Focus: Defining product vision, strategy, and roadmap; understanding customer needs; working with engineering, design, and marketing teams; and using data to inform product decisions and measure success.
Skills to Develop: User personas, market research, A/B testing, data-driven decision-making, strong communication skills, an understanding of the product development lifecycle, and leadership abilities.
Making the Transition: Focus on understanding the "why" behind data requests, get involved in product discussions, work in a product analyst role, and showcase how your analytical skills can drive product strategy. Often, your niche industry/domain experience can be a significant advantage here.
Project Management:
Focus: Planning, executing, and overseeing projects to ensure they are completed on time, within budget, and to the required quality. This involves managing resources, risks, stakeholders, and communication.
Skills to Develop: Strong organizational and planning skills, risk management, stakeholder management, communication, leadership, and familiarity with project management methodologies (e.g., Agile, Scrum).
Making the Transition: Volunteer to manage analytics projects, formalize your project management knowledge through certifications (like PMP from PMI), and highlight your experience in managing timelines, resources, and deliverables in your analytical work.
Charting Your Course: General Advice
Regardless of the specific path you're considering, some universal principles apply:
Continuous Learning: Aside from picking a specific path above, be adaptable. The analytics field is changing rapidly and new paths may emerge. Commit to lifelong learning. Explore new tools, techniques, and concepts regularly.
Build Your Network: Connect with people in the roles or industries you're interested in. Learn from their experiences and seek mentorship. The GOATs community is a great place to start this journey.
Gain Relevant Experience: Look for projects or responsibilities in your current role that align with your desired path. Don't be afraid to step outside your comfort zone.
Showcase Your Skills: Build a portfolio of your work, tailor your resume, and be prepared to articulate how your analyst skills translate to your target role.
What About My Drainers?
I’ve often found that the things that I don’t enjoy doing in my work are usually the ones I don’t understand “why” I’m doing the work.
There are some pretty universal drainers like having to do things that clash with your overall strategy or cost you money without providing any value. In those cases, I think it’s important that we be brave and speak up about these things to stop that work.
Is it mundane or repetitive work that doesn’t really need human interaction? Automate it with technology.
You may just need to dig into those things a bit more to figure out why you don’t like doing them. Some of the drainers that I didn’t understand the “why” behind in the past became work I actually enjoyed once I realized how important the work was.
Finally, if a drainer is part of one of the Paths above that you think is otherwise desirable, you’ll have to ask yourself, “Do the pros outweigh the cons?” Studies vary, but generally you need 3-5 positives to outweigh a single negative.
Final Thoughts
Choosing your career path ultimately is a massive decision, but you can always pivot. However, by being methodical (like a true analytics professional!) you can save yourself years of soul searching or wandering.
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