Why Data Science?
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TL;DR
I’ve always been one for numbers, building, and making an impact.
With a decade of experience in Sales and Marketing Operations and a passion for building efficiencies for businesses small and large, data science is a complementary skill to up-level the possibilities available with this end-to-end data to make Sales and Marketing teams work smarter not harder while (more importantly) creating a positive customer experience.
On a more personal note, my biggest passions are:
- Increasing female representation in leadership
- Increasing save rates and adoption in animal rescue
- Encouraging fitness through the joy and fulfillment it produces as a result
and I want to dedicate any and all of my skills to bringing positive change in these corners of the world.
About Me
When I was younger, math was always one of my favorite subjects; and when I wasn’t in school, I was playing assistant in my dad’s entrepreneurial work and my mom’s day-to-day work for her job and managing the house. For my dad, I would help with purchasing supplies, invoicing, and spot-checking numbers for each — a very early practice in paying attention to detail and the art of QA for me. My mother’s work was also financial and numbers based where I was eyeing over expense reports and writing checks to send in to pay our regular house bills (remember when paying online wasn’t a thing?). Both of these made it so that I was as comfortable in an Excel spreadsheet as Microsoft Paint or KidPix for us Millennials.
One would think this would clearly lead me to study finance, but I also was more of a creative (see: marching/concert band, choir, and arts and crafts kid) — so, marketing became my calling. Many people think marketing is all creative, but the late 00’s was at a point in time where things were especially coming to a head where data actually informed creative. Now it’s undeniable that data is most of marketing. With both data and creative being zones of comfort, it seemed like the obvious choice.
In college, my favorite course was in integrated marketing class where we would research endless marketing publications and Pew research studies to deeply learn about demographic/psychographic audience information to craft the perfect campaign.
Even after college, I loved to read content that was based on data or had a chart in it — one of my favorites being FiveThirtyEight’s “How To Spot a Bachelor Frontrunner” breakdown. It’s a guilty pleasure that can get even more nerdy with data behind it (while also helping when making a bracket for the season). If a curiosity enters my thinking, I know there will always an article (or 10) that will chart the data out. Even now, my partner will read an article and if it is inundated with charts and graphs, he knows to share it — no matter the subject. Give me data, and I’m happy to learn.
But really, why data science?
For any question in the world, data and analysis is the answer. Clearly there is overwhelming amounts of data out there that continues to grow exponentially; and in order to understand it and take action, the art of data science is foundational.
As someone who is dedicated to personal development, a big message that is consistent in the space is to know your WHY. Let’s credit Simon Sinek for being the expert on this; but it’s something almost every blog, podcast, or book comes back to at some point. Your WHY is bigger than yourself and keeps you motivated through hard things — like the process learning a completely new skill. The following are a couple of my motivators.
- Always growing: data science as a complementary skill
My expertise is Marketing Operations and Sales Operations. Not only does this involve orchestrating end to end system functionality, but making the environment more efficient with process and automation. Most of the time the latter portion involves in-depth reporting.
At a higher level, this reporting and analysis helps find the biggest blockers to game-changing efficiency in the pipelines, marketing funnels, leads, or sales overall. Strategically, the results from this analysis are key, playing a role in prioritization, budgeting, and resourcing. At the other extreme, if we zoom in to the usefulness of building the next best version of the systems that be, analysis provides the QA check (oh hey, my childhood practice coming into play). Without this in-depth QA process, your new system could launch you into new and possibly more technical problem.
My roles have been in start-ups for the majority of my career with only two corporate companies including my current role. These two giants have taught me that the data that was manageable in CRM systems within start-up world sometimes isn’t as accessible or malleable when managing 40K+ users. They are stored in complete data warehouses with more data than is comprehensible, but it is ripe for the picking and data analysis (with proper privacy regulations and access guardrails, of course).
Thus, in order to grow within my skill set and have a more informed strategic view of the systems and data at these larger companies, along with the opportunity to make this data trove work further for efficiency (higher revenue, better prediction, better customer experience in product marketing or sales) data science is the perfect next level of education.
When looking at the data science process, it’s essentially what I have been executing in all of my roles; but at a grander and more efficient scale. Efficiency is a way of life for me, so data science is my next best step to making my own self more efficient!
2. Positive impact: data science as a world-changer
I hinted at this within the last section, but I want to create impact anywhere I am. Whenever I can bring my skill set and create a difference for others whether inside or outside an organization, I am most fulfilled.
This also means non-profits. My main passions are:
- Increasing female representation in leadership
- Increasing save rates and adoption in animal rescue
- Encouraging fitness through the joy and fulfillment it produces as a result
Even writing out each of these my brain lists through all the data available for each of these, the studies that I’ve read, and the vision of what I know I could do with knowledge of data science. Could I bring the next big idea or group or project to light that would make a positive difference to any of these areas? With the motivation and heart I have behind these things, I know I can.
Conclusion
Back to the personal development world — many times different strategies are referred to as “tools in the tool belt”. Throughout my career and life I have amassed a handful of these, and data science is the next one on my list. It’s another milestone of my growth, brings a different perspective to analyze any challenge, and I personally look forward to contributing to the world by utilizing it for the better.
