Mentors & Experts

Mentoring is best described as an educational process when mentors share knowledge with the purpose of surfacing potential in their protégés.

  • Gareth-Cox-Thorpe-Data-Analytics-track-mentor

    In this interview, we’re speaking with Gareth, a data analyst with 10 years of experience in the tech industry. Originally from the UK, Gareth’s journey into data began unexpectedly, driven […]

    In this interview, we’re speaking with Gareth, a data analyst with 10 years of experience in the tech industry. Originally from the UK, Gareth’s journey into data began unexpectedly, driven by curiosity and a hands-on approach. Now based in Lithuania, he works as a Senior Sales Data Analyst at NordPass, part of Nord Security, a leading cybersecurity solutions provider.

    Gareth discusses his career path, the challenges he’s overcome, and his passion for mentoring, offering a unique perspective on the evolving world of data analytics.

    Gareth-Cox-Thorpe-Data-Analytics-track-mentor

    Can you briefly introduce yourself and share your background in the tech industry? What sparked your interest in pursuing this career path?

    I’m originally from the UK but moved to Lithuania with my wife and cat at the end of 2021. I’ve been working in data for 10 years, which is crazy to realize how fast time has gone!

    I would say my journey into working with data wasn’t as deliberate as most. I was working as a tracer for a debt purchasing company, and a few of my colleagues were using SAS within their jobs. I found it fascinating to see how they could write a script and easily manipulate data. So I started playing around with Excel, which led me to create a team tracker for the tracing team. Around this time, I also remember buying an Excel 2010 for Dummies book, but after reading a few pages while on the train, I never picked it up again. I’ve always found the best way to learn is to get on with it, make mistakes, and then learn how to fix them!

    I then moved into a Junior Analyst position at a different company and discovered SQL, Qlikview, and Tableau. This is where I really found my passion, as I loved creating data products that delivered value for the whole company, such as understanding buying patterns and retention rates. After a couple of years, I moved on to my last role in the UK, which involved working with customer experience data. I was analyzing feedback from insurance customers and using this data to improve customer journeys and conversion rates.

    And then the world got turned upside down with the pandemic, and my wife and I decided that we wanted to try and live somewhere else. With my wife being Lithuanian, Vilnius seemed like a good option, so here I am working as a Senior Sales Data Analyst for NordPass. Nord Security in general is quite different from my previous UK company. It’s a younger, more agile start-up, which creates more excitement but also more challenges, and it’s where I discovered a desire for mentoring and Women Go Tech.

    Have you encountered any significant challenges or obstacles in your career? How did you overcome them?

    This is an easy one for me. Moving to Lithuania and working in a different culture has been the biggest challenge. I remember when I first started and got quite a big shock due to me not knowing the language. Obviously, all of the company communication is in English, but the small chats in the kitchen that I couldn’t initially get involved with were a strange experience. However, this has also been the reason why my Lithuanian has improved since moving over here.

    You’re currently working as a Senior Data Analyst at Nord Security. Can you tell us more about your role and what aspects of it you find most exciting?

    My role at Nord Security is to analyze the B2B data of NordPass. I’ve recently been leading a project to rebuild the B2B data, which has included working with our data engineer on the backend data tables and then rebuilding the company-wide dashboards. I’m now wanting the whole data team to start using this data to provide insights to the different teams of NordPass. Insight delivery is very important, and I think a good analyst provides answers that haven’t been asked yet.

    Are there any new trends, tools, technologies, or methodologies in the data analytics field that you find particularly promising or exciting?

    I’m guessing you’re going to hear this answer a lot, but AI is the biggest thing at the moment. Even just using ChatGPT to correct or optimize your code is going to speed up analytical work so much. As analysts, I don’t think we should fear AI, I believe we should be using it to enhance our jobs.

    The competition for entry-level positions in data analysis is quite intense nowadays. What are the top three skills that aspiring data analysts should develop to stand out in this field?

    1. Persistence—don’t just think, “It can’t be done.” Instead, have the attitude that there’s always a way.
    2. SQL—get good with this. A lot of smaller data teams probably won’t have a data engineer, so if you’re an analyst, you’ll also be expected to do backend work.
    3. Presentation skills—a lot of data people tend to be more introverted and don’t like doing presentations. If you get good at giving presentations, you’ll definitely stand out.

    Do you have any advice for someone already working in this field who is looking to progress to a senior role? What helped you make this move?

    Mentoring has helped me a lot, and I think as a senior, your responsibilities should include helping more junior analysts improve. You also need to develop confidence in your experience and skills, without it, you won’t be able to offer your advice to the company you work for.

    How do you approach personal development and continuous learning in your career, and how do you keep up with changes in the field?

    Don’t wait around for your manager or company to help you improve—you need to be proactive and work on this yourself. I’ve used Udemy or Coursera courses, and I also put myself on this Women Go Tech mentoring programme. Doing these things myself is how I’ve developed throughout my career. Also, when you’ve completed a course, shout about it on social media so people can see!

    Can you share a recent book, podcast, or resource that has positively impacted your professional growth?

    There’s two people that I follow that come to mind. One is Gary Vaynerchuk, he’s an entrepreneur who specializes in marketing. He often creates content around digital marketing but also more generic things such as what to do if you don’t know what you want to do in your career. The other person is Jesse Itzler, I actually found Jesse as he was a guest on Gary V’s podcast. He’s a guy that wants to do it all! He’s founded many successful companies but also overcome some huge personal challenges such as running a 100 mile race in 24 hours!

    Why did you decide to become a mentor?

    I’ve always liked giving advice and love helping junior analysts with their work so thought I would increase the opportunity to do this.

    You’re currently mentoring two mentees. Can you share some highlights of your mentoring experience with them?

    My mentees are at different stages of their career. Vitalija is not afraid of putting herself out there. She’s doing podcasts and talks at conferences. So the highlights from my time working with her is when she’s sharing one of her talks and then working on her content together. Julija has made a complete career change so she’s earlier in her analytical career. She’s currently studying with Turing College. My highlight with her is seeing how passionate she is when presenting her dashboard work to me which she got top marks for!

    Finally, what advice can you give to other mentors?

    I feel like I’ve learnt as much as my mentees, so my advice to other mentors would be to also be open to learning during the programme.

    Curious to learn about the experiences of Gareth’s mentees? Read Julija’s and Vitalija’s stories here and here

  • Mentor in The Spotlight Mike Mateev - Women Go Tech

    Mike Matveev, the CTO and CDO at B9, has been at the forefront of data analytics for over a decade, navigating the evolving tech landscape from a junior position to […]

    Mike Matveev, the CTO and CDO at B9, has been at the forefront of data analytics for over a decade, navigating the evolving tech landscape from a junior position to top management. Now, he’s channeling his rich experience into mentoring, focusing on empowering women in tech through the Women in Tech mentorship program. 

    In this candid conversation, Mike discusses the transformative power of sharing knowledge, strategies for overcoming career hurdles, and why tech expertise alone isn’t enough to succeed in today’s dynamic industry.

    How did you get the idea to become a mentor?

    My journey in Data Analytics began 14 years ago. I started from a junior position and then went through all the circles of hell! I’m just kidding, of course, yet every joke has a bit of truth. 

    I was lucky to have my mentor, who helped me dive into the world of data and look at it from the right perspective. At the time, there were no online academies or courses, so he helped me find books and websites to gain knowledge bit by bit. In my career, I have always learned from other people, asking questions, simply following their steps, and implementing their best practices in my own work. One of the most inspiring examples was my manager at the Binbank team – a lady with incredible technical skills. She taught me to stand for my point of view, to take risks, and to try new things. Now it’s my turn to pay back and help others!

    What job issues can be better approached or solved with a mentor’s help?

    I started in the banking sphere and have been in different functions – from collection department to sales, product development, operations, marketing, etc. Both in large banks and fast-growing startups in more than 8 countries. I would say despite location, corporate culture, and mission, every banking business has similar “pains”:

    – misunderstanding between functions

    – inaccurate requirement language

    – chaos in teams’ work (waterfall of urgent tasks)

    – lack of profound goal-setting and shared vision

    In other words, bad management and miscommunications can ruin a promising project even if the competence of the IT team is extremely high.

    Data analysts are often treated as supportive IT workers. How can mentorship help a person overcome this stereotype? 

    For me, an analyst is not just a “service worker” but a specialist who understands a particular business area and can advise the best solution to the function leader. In fact, becoming his partner in finding new ways to boost the processes. Data analysts are the ones who see new directions, open new doors to the teams, and notice subtle signals.

    I know many people who are so much focused on technical development that they just don’t see other opportunities lying in their hands. 

    Sometimes development is not about getting as much new knowledge as you can, it’s about posing the right question. And this is the moment when a mentor can be really helpful!

    In general, my motto is “If you face a problem, most likely it has already been solved, and you just need to find those clues and guides!”. Go ahead and just Google it!

    How is the mentorship process organized?

    It has some formal structure, such as an introduction, discussion of expectations, goal setting, building a framework, etc. We schedule meetings, communicate in chats, share useful links, and discuss particular issues. The whole mentorship lasts from 3 to 6 months, and the progress is always tracked.

    At the same time, mentorship is mainly based on a personal approach, sharing experience, giving advice, and developing a leader’s skills. To make the process smooth and pleasant, you need to build trust and good contact. When the mentee opens up, the whole thing goes easier and much quicker.

    How did you understand the idea that it’s time to share your experience?

    You just start to notice it in your daily working routine: how helpful you could be, how you could guide the newcomers, guiding them to achieve their goals without mistakes, extra efforts and even burnouts. You cannot help but think about it again and again!

    Globally, despite the so-called technical development, ChatGPT, and other AI innovations, the data analytics market is still very small. Sometimes it takes up to 6 months or more to find a good specialist. So it’s crucial to help the new people realize what hard and soft skills they need to develop to succeed. And it’s very rewarding, too – you are building the industry! 

    Why did you join the project supporting women in tech?

    There are stereotypes that IT is a male-dominated field, which can lead to biased views from colleagues and employers. Women often have to prove their competence and professionalism more than men. Very often teams in IT companies are mostly male, this can create difficulties in communication and adaptation for women, affect their comfort and work efficiency. I have always had women in my teams and in neighboring technical functions, yet frankly speaking gender ratio was never 50/50. I believe women have huge potential in tech. 

    You started your career at the beginning of the data analysis era. Don’t you think that the newcomers face different problems? 

    I’m self-taught and have come a long way. Often, I was literally learning from my tries and mistakes, sometimes being too shy to ask, not really knowing the operations, or lacking technical skills. I believe all the cases I’ve been through can be very helpful to newcomers. Mentees can learn from me and not waste their time going through the same typical cases.

    Also, I’d say some people need technical advice, while others have to learn basic communication tips. Mentorship is really an individual process!

    The tech industry has a lot to offer nowadays, and one can try him/herself in different directions to understand exactly what he or she wants. You have so many educational programs that your eyes run wild. Yet a certificate of completed course does not grant you employment. You need to prove your experience by compiling a portfolio, for example, using Gitlab to upload your projects in Python or r. A good mentor can guide you on that path and help you succeed.

    What are the top 3 personal qualities and skills essential for a data analyst?

    As for the personal skills, I would say these are:

    1. Persistence

    2. Commitment to learning and development

    3. Having a “peripheral view”, meaning that you should always look wider than what you need and examine the situation from different angles 

    As for the crucial technical skills:

    1. Analytical skills – ability to analyze data, identify trends, ability to find weaknesses, notice inaccuracies

    2. Technical skills in programming and analytics, minimum: SQL, Excel(+DAX) and a plus: Python, R

    3. Understanding of business processes – the ability to understand documentation and diagrams, and correlate it with data.


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