Mentoring without borders – growing data science skills internationally

 

Applications opened for the International Data Science Accelerator Programme for the first time on 31 January.

The programme has been set up to help analysts from National Statistical Offices (NSOs) who are looking to improve their data science skills and potentially become a data scientist in the future.

Our teams have been working successfully with international organisations to build data science skills and capacity for some time. For example, our data science hub based at the Foreign, Commonwealth and Development Office (FCDO) has spent the last 18 months mentoring colleagues in Vanuatu. This has not only helped to significantly improve the way they produce vital statistics, but they now have the skills to support this work internally by mentoring others.

Building on the successful UK Data Science and Data Visualisation Accelerator programmes, we have developed the programme in collaboration with the United Nations (UN) Big Data Task Team on Training, Competencies and Capacity Development, so other NSOs can realise the benefits of data science mentoring.

While there was significant interest, setting up a remote mentoring programme across different countries and time zones was not without its challenges. To ensure we could run it effectively, we launched a 12-week pilot from 13 September to 3 December 2021. This involved four pairs of international mentors and mentees from various parts of the world (Ghana, Zimbabwe, Vietnam, Poland, Jordan and United Arab Emirates (UAE), coming together to add to the global development of Data Science.

A graduation event was held in December 2021. National Statistician Ian Diamond, one of several high-profile speakers, offered his congratulations to the participants and expressed his support for this exciting initiative.

In the final part of our Accelerator blog series, we spoke to Fatima Al Taharhwa (Department of Statistics, Jordan) and her mentor Hatem El Sherif (Federal Competitiveness and Statistics Centre, United Arab Emirates), who took part in the pilot programme.

Fatima tells us what her accelerator project was about:

“My project involved automating the data coding for various statistical classification activities, using Natural Language Processing and machine learning techniques.

In the Department of Statistics in Jordan, we collect some data fields as text (Arabic text) such as occupation, scientific specialisation, and economic activity. These data fields must be transformed into a specific international or local standard coding. Usually, this is done manually by a specialised technical team as a one-off data cleaning and preparation stage. This process is costly, needs effort, and time-consuming.

My aim was to try to automate and speed up this process by using new methods and develop the workflow.”

Remote mentoring can be challenging, particularly if there are difficulties with connections, or participants are in different time zones. Fatima and Hatem explain how they overcame these.

Fatima: “Our main challenges were time, and sometimes, the (internet) connection. It has been a challenge for both of us to find enough time to dedicate to this project. Our mentor inspired and guided us with his help and expertise. He managed to show us the easiest and most efficient path to solve some of the issues we faced and learn new techniques and tips to perform at a higher level. Flexibility from both sides meant that when the connection was bad, we rescheduled our meetings and managed to ensure we were not losing time.”

Hatem: “Patience and realistic expectations are the key to ensuring any challenges are approached proactively, rather than worrying or stalling. We also discussed and created a solid plan with achievable goals in the timeframe given. That helped us to be clear on what we need to make our collaboration most efficient.”

Pairing mentees and mentors from different organisations can help participants gain new skills and perspectives. So, what did Fatima and Hatem get out of their mentoring relationship?

Fatima: “I am studying a data science masters and I aim to improve the work of my department using modern technologies, such as machine-learning, over some traditional methods.

My department faces many challenges that make moving forward in this field difficult, despite the necessity for developing new work methods to keep up with the world, such as investing in modern technology to get the best results. Through this project, I managed to improve my skills in planning clear methodology for all stages of the project, by using professional tools like Chrisp. I discovered new open-source tools, and learnt when, why, which tool or software to choose.”

Hatem: “It has given me great joy working with such a great and hardworking team. I am inspired by their determination and desire to learn, and pleased I managed to guide them to progress in the field. In the end, a mentor needs to guide and not drive, and this team of mentees has responded beautifully to any direction given.”

The mentor and mentee’s organisations can benefit from the time they invest in the International Data Science Accelerator Programme. So how did it Fatima and Hatem’s time on the programme benefit their organisations?

Fatima: “Our department learned a lot from this collaboration. We’ve insisted on having as many representatives from across the organisation involved in this, as it can help us develop a lot. We managed to get the right attention from our seniors, and they are now supporting us more in developing, implementing, and sustaining data science work within the organisation.”

Hatem: “As our data department is working on becoming a regional hub, working with mentees from Jordan has created a solid bridge between the two departments. Our collaboration will continue in the future and hopefully become stronger and stronger.”

What advice do Fatima and Hatem have for colleagues and their organisations considering applying for the programme?

Fatima: “Definitely go for it! For us, it has been a great opportunity. We received so much in just 12 weeks and managed to learn a lot. It’s brilliantly coordinated and provides a quality experience.”

Hatem: “The International Data Science Accelerator Programme is a much-needed international initiative in this field. I am certain that any data science department around the globe will benefit from more insight and examples of how others are approaching, developing, and growing. Mentoring is a great way to do that – sharing experience, knowledge, and accessing a global platform where we can all help each other.”

Applications are open for the International Data Science Accelerator until 28 February 2022. The programme will start on 28 March 2022 and end on the 17 June 2022. Our dedicated International Data Science Accelerator Programme web page has all the information you need, including the application forms for you to apply as a mentee or a mentor. You can contact the team if you have any questions or are not sure if the programme is right for you.

You can also read the other posts in our Accelerator blog series.


Updated 3 March 2022

Mentee applications are now open until 7 March.

The deadline for mentor applications has been extended until 15 March.