How Sarah Mestiri Transitioned from a Software Engineer to a Data Scientist

Christopher Dossman
4 min readMar 28, 2020

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Almost 3 years ago, Sarah took the decision to quit her job as a software engineer and started working towards becoming a machine learning expert. Along her journey, she came across my series on becoming a machine learning engineer. We connected and I started offering her mentorship.

Now working as a Data Scientist at Remerge GmbH, a mobile App Retargeting company in Berlin, Germany, Sarah is on a mission to make people’s lives better by shaping the latest technologies to build solutions that solve real-world problems.

Here’s a short interview I did with her a while ago. Read to the end and get inspired.

Q. Who is Sarah and where are you in life now?

Answer: Sarah is a Software Engineer from Tunisia turned Data Scientist. I’m currently working and living in Berlin, Germany.

Q. What is your current job like?

Answer: I work as a Data Scientist at Remerge GmbH, a mobile App Retargeting company in Berlin, Germany. The one thing I love about my work and career is the ability to create software products that have an impact on people and society at large.

At Remerge, we are a team of data scientists and we handle different projects at a given time. Working as a Data Scientist is challenging as I have discovered it is different from software engineering. As a data scientist, you have to know and understand the business domain more. You also need to have statistics knowledge. As a software developer, I used Java IDEs but now I have switched to Python and Jupyter Notebooks for data exploration and algorithm modeling.

I’m currently working on a recommender system using Item-Item collaborative filtering.

Q: Where were you about 3–5 years ago?

Answer: I graduated in 2014 and started looking for a job because I wanted to practice what I learned by developing software projects. I started my first job as an SAP developer working for SAP clients. One year into the job, I felt out of place as I wasn’t in the core business development of the SAP product.

It is then that I decided to do a Java SE Programmer Certified Professional certificate and look for a Java-based developer job. I loved Java and it is more marketable. I finished the certificate and I got a job as a full stack developer in FIS, a finance-based company as a software engineer.

At FIS, I found myself working on front-end web-based applications using Angularjs. However, I wanted more and my desire was to do more of backend development. I also wanted to connect with the products I’m developing. In school, I was always thinking about artificial intelligence, machine learning and was always inspired by face recognition and the recommendations we find on the Internet.

I quit my job and decided to pursue data science and machine learning. I also attended a Data Natives conference in Berlin that covers tech trends and innovations in big data and machine learning. The result was that I connected with a lot of people on social media who I shared my learning goals, experience and challenges with and a myriad of interesting articles about AI and machine learning. I started by creating a plan and enrolled for online courses and later working on projects. After some time, I was ready to search for jobs and that’s how I ended up at Remerge as a data scientist.

Q: What were some of the biggest obstacles you have faced to get to where you are now?

Answer: It was not easy to switch from software engineering to Data Science. But I did it. I have written a lot about my machine learning journey on my blog.

Q: What kind of advice would you give to people who want to transition into another career? For example, switching into data science and machine learning?

Don’t do it because other people are doing it, it’s important to know why.

First, ask yourself why you want to change careers. From there, you can explore different careers and specific AI domains that you would be interested in.

Secondly, have a plan. I believe that without a plan, you cannot stick to your goals whenever you face some ‘down’ moments. Choose the right courses and make sure you have a time estimate for when you complete them. Also, don’t just rely on online courses or bury yourself in books the entire learning period. Jump in and start work on projects as soon as possible. Learning to explore data and algorithms while you are still learning which will help you make better progress.

Q: What do you hope you achieve in the next 3 to 5 years?

Answer: I want to gain more knowledge of working in recommender systems and become an expert in the field. I’m greatly interested in how data science is applied to recommender systems. Again, they are all over the Internet and are increasingly being used for many tasks.

Q: Would you like to become a mentor? We have a program where we want to match promising AI students with successful mentors.

Answer: Of course. I would love and want to experience mentoring young people.

Here are two posts by Sarah connected to her story that will greatly inspire you.

✔ What Helped me Get a Data Science Job that Fits my Ambitions — [Part 1]

✔What Helped me Get a Data Science Job that Fits my Ambitions? — [Part 2]

Connect with Sarah

Thank you for reading! I value your comments and shares and would love to connect on Twitter, LinkedIn, and Facebook. For updates on the most recent and interesting Machine Learning research papers out there and stories like these, subscribe to AI Scholar Weekly.

For mentorship towards becoming a machine learning expert, reach out t me on cdossman91@gmail.com or tweet at @cdossman

Please 👏 if you enjoyed this article. Cheers!

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