A data science mentor is a person who provides guidance, support, and feedback to someone who is learning data science or looking to advance their skills and knowledge in this field. A mentor might offer advice on coursework or projects, help the mentee develop a learning plan or career roadmap, or provide support and encouragement during times of frustration or uncertainty.
Some specific things a data science mentor might do include:
• Guiding on coursework or projects: A mentor can help a mentee understand complex concepts, offer suggestions for how to approach a problem or project, and provide feedback on their work.
• Helping the mentee develop a learning plan: A mentor can work with the mentee to identify their goals and objectives in data science, and help them create a plan for achieving those goals. This might involve recommending specific courses or resources, or helping the mentee create a schedule for learning and practising.
• Providing support and encouragement: Data science can be a challenging field, and it can be easy to become discouraged or overwhelmed. A mentor can provide support and encouragement to help the mentee stay motivated and on track.
• Offering advice on career development: A mentor can help the mentee understand what it takes to succeed in data science, and offer advice on how to build the skills and experience needed to pursue their goals. This might involve helping the mentee identify opportunities for internships, projects, or jobs, or providing guidance on how to prepare for interviews or negotiate job offers.
What is mentoring?
Wiki says: “Mentorship is the influence, guidance, or direction given by a mentor. A mentor is someone who teaches or gives help and advice to a less experienced and often younger person. In an organisational setting, a mentor influences the personal and professional growth of a mentee. Most traditional mentorships involve having senior employees mentor more junior employees, but mentors do not necessarily have to be more senior than the people they mentor. What matters is that mentors have an experience that others can learn from.”
How can mentoring help you?
Mentoring is like a student-teacher relationship. In Data Science, a mentor can be a Senior/Consultant Data Scientist who will answer your questions and raise questions you hadn’t considered to help you meet a certain objective/skill/master a specific tool.
I had mentors while working for Symantec and DELL as these companies had formal mentoring programs running. The “issue” was that they were not Analytics / Data Science specific, and, at that time I needed domain-specific support. To fill this need, I went on LinkedIn (as they try to promote professionals as mentors), but the people I contacted did not reply or they were very expeditive. I looked deeper and I found these guys: MentorCruise. They are a dedicated website for mentoring services. I found them cool and I registered as a Mentor myself.
Having a mentor and being one will give you confidence and great satisfaction that you can help other professionals similar to you. At the moment I’m mentoring five data professionals. I like the interaction and the feedback I got so far.
While working for Symantec, I attended a 3 days course on coaching and I got to experience being both a coach and a coachee. Nowadays, there are more in-depth specialisations and coaching is a profession. I wanted you to learn about coaching from the best, so I asked a former colleague of mine who is a trained coach to guest post for www.thebabydatascientist.com .
Claudia is a Positive Psychologist and Coach specialising in career and leadership coaching for people in tech. She is based in Ireland and works globally with people who want to be happier at work.
Let’s see what Claudia advises:
What is coaching?
Coaching can be defined in many ways. In essence, coaching is a space for personal development through a thought-provoking and creative process that inspires you to maximise your personal and professional potential (International Coaching Federation).
In the business world, workplace coaching is often used as an effective tool to optimise performance and unlocking untapped potential. Often, the goal of coaching interventions in the workplace is to build team cohesion, employee productivity and motivation, and develop authentic leadership skills.
However, coaching is much more than just a tool to increase your productivity. Coaching is a journey to more self-awareness, a space to help you learn more about yourself. Typically you will gain a greater understanding of values and your strengths and learn how they impact your behaviour, your thought processes and your emotions.
There is great power in understanding that triangular relationship – it’s the starting point to self-determined behavioural change.
How is coaching different from mentoring?
Coaching is built on the core belief that you, the coach or the client, already have all the answers, skills and knowledge within yourself to reach your goals. The coach’s role then is to help you uncover the answers you are seeking through a non-directive and non-judgmental dialogue.
That means coaching is less directive than mentoring. It is not about giving advice, it is about empowering you to discover what is best for you – in work and in life. While a mentor shares their own experiences and industry knowledge with the mentee, a coach is not necessarily an expert in your line of work. A coach asks you thought-provoking questions, offers new perspectives and guides you in the process to come to a new insight that empowers you to create a path forward that is right for you.
How can coaching help you?
Coaching is a very versatile approach to personal development and can help you achieve goals, make difficult decisions or face challenges with more confidence. Below are a few examples of typical coaching topics for career coaching.
You can read more on my blog: https://thebabydatascientist.com/the-benefits-of-having-a-coach-mentor-in-the-field-of-data-science/