I left a cushy position at Facebook after just two years to start my own data analysis and visualization consultancy.
It was a huge decision to make, but I felt that I had to.
My colleagues had been so supportive and encouraged me to get involved with data science and visualization, and I wanted to do my part to help them achieve their dreams.
I was inspired by how well their work is done, and how quickly they have grown into well-respected leaders in the field.
I had never been involved in the world of data science or visualization before I started my own consultancy, and it was the first time I had spent a large portion of my career doing something that was not directly related to my job.
So I had never really felt comfortable in the way that people view data, or how it was presented in the media.
I had no idea what I was doing was really a serious job, so I wanted as much freedom as I could in terms of my own thinking, my own goals and my own path.
To my surprise, it turned out that my own career trajectory was pretty unique.
At the time, I had just left a job that was a lot more challenging and focused on creating compelling, compelling experiences, so there was no need to get up early to get an early start on the next big thing.
I started my first data analysis project at Google, and by the end of the project, I was convinced that data science could actually help solve the world’s most pressing problems.
The first thing I did when I left Google was to hire a data visualization expert to help me write a new presentation for a big event, and he spent a couple of months in the same office, writing a presentation for me, and then I got him to write an extension to my new presentation.
In that time, he also became the Data Scientist on my team, and we started working together on a lot of new projects.
So, from there, it’s been a very rewarding journey.
When I was first starting out at Google in 2010, I didn’t know a lot about data science, but after I had built a successful data analysis consultancy, I realized that data was one of the most important topics in the data world.
As a result, I got a lot out of data analysis, and data visualization was a natural next step.
But I was not sure that I was ready to tackle data as a profession, so my first major project was to start a data analytics startup, which I ended up buying in 2012.
Then, after I left Facebook, I went back to my previous career and started my consultancy in 2014, which is how I ended the following year.
So, after leaving Facebook, what was the biggest change in my life?
First, I decided to get married and start a family.
I was married for eight years, and at that point, my husband and I started to look at the data more seriously, and the data science that we had developed was a big part of it.
I really felt that my husband was a much better data scientist than I had ever been, and that my career was on the right track.
I also made a huge commitment to the people in my professional life, so that I could support them through all the ups and downs of my professional career.
We had a very stable, supportive and rewarding family, and my family also supported me in my decision to move to a data science consultancy.
I got to travel all over the world with them, and they supported me with the travel, accommodation and living costs, and also made sure I was always in touch with them.
Finally, I started learning data science from other people and learning about the world around me.
During my first few years in data science I was very familiar with data, but it wasn’t until I got involved with the business world that I started having real impact.
I started working at a company that I actually wanted to be involved in.
Since then, I’ve learned a lot and built a lot on my own, and over the past three years I’ve been doing a lot to build up my own brand.
I’m really proud of what I’ve achieved.
The next step for me was to take the data visualization world a step further.
For a long time, there wasn’t a single, unified approach to data visualization, so the big data companies have been very busy developing and delivering new approaches to data, which has helped drive a lot adoption in the industry.
Over the past two years, we have also had the launch of a new research platform that helps companies better understand how they can use data to make better decisions, and this has led to a lot innovation in the analytics space.
Data visualization is now the most popular type of visualization in