Sometimes I had no idea what presenters were talking about, however I felt like this was I place I belonged. I can clean a csv file and run k-means clustering, random forests, or logistic regression. However, this was real data science. I appreciate the detail and the processes of company scale projects. I like that the talks were fairly detailed and technical. Entering into this field it is important to get a feel of the level of depth and expertise required. At some points I was seriously questioning and doubting myself. Why was I here when I can't understand what they are talking about? Is it even possible for me to get to the point of understanding?
What is so great about data science and tech field generally that if you don't know something its fine because you know that you can learn it. Tech field has taught me that you are never too old or past your time to learn something new. Just think about it, there are students starting on data science / analytics courses now that will be looking and getting jobs in 1 to 2 years. At any point in your life you can put in the work and time to learn something new and be equally competitive. It's not going to be easy, it will be quite difficult and challenging, but it is possible.
If you are even just curious or considering going down the path of Data Science - a conference is a great way to get a grasp of this field as it is happening right now. You get exposure to this industry across the spectrum and see real applications on a large scale. Conferences give you insight into the culture of the field. Exposure is very important. Not long ago I posted onto Women Who Code slack group that I was feeling insecure and feeling guilty for receiving a scholarship to attend an Angular conference when I don't know anything about Angular. Women Who Code members jumped right on my comment and said:
Yeah, I’ll be there and have never used Angular. The most value at a conference, I think, comes from the connections you make with people. So feel free to skip some talks and do the ‘hallway track’ or jump into some crazy over your head talks to see what other cool things people are doing and talk to the speaker after.
No matter the subject you observe how people present themselves, how people engage with you, and what people are interested in. People were wonderfully engaging, asking, "What sort of projects are you working on?" or "What do you do?" while standing in line for lunch and each person introducing themselves at the lunch table. When I said I work for a local city government and I do GIS - Geographic Information Systems (maps), people thought it was interesting and I had a lot of fun talking about how GIS concepts relate to Data Science. This is what you expect out of a conference, talking and networking, but this is not always a given. When a conference is approachable and friendly this is something to be appreciated, it is not always like this. There was a great variety of expertise. Some were taking online courses and getting started, some were getting Masters degrees in data and analytics, and some were working, professional, data scientists. I could just as easily talk with a newbie as much as superstar data scientists. There were a good amount of university students, more so than other tech conferences.
Data Science stems from academics compared to other tech fields such as UX/UI or web development. I recently attended the Women Who Code WeRise Tech Conference and Jennifer Bland started off the conference talking about how this revolution in technology and women entering technology is very self-taught and blossoming from coding boot camps. By great numbers women are taking risks, investing in themselves, acquiring skills, and becoming industry experts and leaders in technology in the past few years. Breaking into Data Science on the self-taught and boot camp route is even more difficult. A Data Scientist is a unique person that can code like no other, knows how to apply advanced predictive statistics, and knows what to do with large disparate volumes of data. It is not easy at all, however the industry culture is even less adaptive and encouraging of boot-camps. A boot camp is not going to be enough to get you a web development job either but once you build projects and prove you can do things, then you are on the market. If you get a foundation in a boot camp then make Kaggle projects, and build your portfolio, I believe you will "get in." The thing is, there is room for everyone. If you hypothetically know 20% of data science you are already very valuable because analytical skills and programming are valuable to every single industry. You may not be ready for Lyft or Google, but literally every industry needs data and analytical support.
I love the mutual support culture of the tech industry. Often a presenter would state that they welcome advice and recommendations on how to better what they are working on. Data Science is not new at all but this dramatic expansion and ever growing applications are new. There are always new ways to use algorithms and new ways to sense data. We can see, touch, taste, feel and now even sense information and data about objects, ourselves, and the world around us (after going through a workflow and data pipeline of course.) We are all learning this and it only makes the field and the applications stronger as people learn from each other and continue to push the boundaries of what is possible. There is room for everyone and we have to continue removing barriers to this career path and provide opportunity to people to get to the door. I attended the SDSC on a MailChimp scholarship, and have taken some big steps in my career since attending.
Data Science is rooted in people. It is rooted in data but of course people are creating the data. I don't just mean people are creating data such as putting numbers on a spreadsheet, people's daily actions are data, our clicks, our purchases, our locations visited. This is a people industry made up of humans and human actions. The ethical AI presentation by Rumman Chowdhury left a big impression on me. It is essential that algorithms and processes developed by data scientists are fair and transparent as possible. A great point she made is that "Data is not an objective truth. It's a reflection of preexisting institutional, cultural & societal biases." The data does not tell what to do, people design what data is used, how it is transformed, and how it is interpreted. As companies and especially governments get excited about using data to make better decisions, it is important to weigh in the risk of bias. If you can use algorithms to fix pot-holes, the risk is low and the potential usefulness for the city could be high. If you are using facial recognition for Immigration Customs Enforcement the risk for bias is extremely high and should honestly be shut down.
The world is rapidly changing and data is rapidly being created. Data is the new oil and I am out here finding my place it in.
Post Southern Data Science Conference there have been a series of fortunate career building events in my life!
I participated in my first ever hackathon and our team won! We were two programmers, and two traditional government GIS people competing against teams of data scientists and software engineers.
I then gave a presentation to Atlanta Regional Geospatial Community meeting about the hackathon experience and how GIS is a perfect launching pad career into data science because location intelligence has transformative (and winning) concepts in data science world.
I then interviewed with my dream job, I got a call back for a second interview, gave a data presentation for my interview, and got a job offer! I accepted a job offer as a data analyst with Habitat for Humanity!
I then presented at Women Who Code WeRise tech conference on how concepts of set theory build a bridge between GIS and Data Science.
I took a part-time Data Science boot camp a year and a half ago. I am not a "data scientist" from the boot camp but it helped me to expand upon my GIS career and take my skills and my mental concepts about data to the next level on the graph of my life.
Networking, boot camps, online courses, conference, hackathons, making presentations, every touchpoint in your career development matters you don't always see results right away just keep making edges and nodes connections!