What are the best ways to find a mentor in data science as a woman?

Existem várias organiza??es e grupos dedicados a mulheres na área de tecnologia. Participar dessas comunidades online ou em eventos presenciais pode ser uma ótima maneira de conhecer profissionais experientes que podem se tornar mentoras. Além disso, os eventos e comunidades proporcionam networking, o que tende a agregar na troca de conhecimento, rede de apoio, até ajudar a conseguir emprego.

Finding a mentor is crucial for getting started with Data Science. Listing your goals and actions towards them side-by-side are key to finding a good mentor who can complement well with you and also help you setup a correct path for success in the field.

Once your data science goals are clear, finding a mentor as a woman involves active networking. Attend industry events, focusing on diversity and inclusion. Use online platforms like LinkedIn to connect with professionals and express your eagerness to learn. Engage in women in tech groups or mentorship programs tailored for data science. Remember, mentorship is a two-way street, so be ready to offer your skills in return, fostering a mutually beneficial relationship for growth in the field.

It is all about observing the people around you and identifying any skills that they excel in that you would like to get better at. Most people enjoy helping others, so voicing to them what you would like to learn and asking for their help usually does the trick.

Acredito que quando uma mulher busca uma mentora é porque existe uma confian?a e conforto maior durante esse processo. Receber mentoria é pode ser algo material, onde se fala sobre metas, resultados e performance, mas a verdade é que também se fala sobre medos e inseguran?as no campo pessoal e profissional. Ent?o, além de listar os objetivos materiais, liste suas quest?es subjetivas que levam a buscar uma mentora.

Women-focused circuits: Join communities like Women in Data Science (WiDS) Worldwide, R-Ladies, and Women in Machine Learning & Data Science (WiMLDS) to network and learn from experienced women. Professional organizations: Look for college-wide chapters of ACM-W (Association for Computing Machinery Women), LeanIn by Meta, and Codess Cafe to connect with local women in tech. LinkedIn: Utilize LinkedIn to find data science professionals you admire. Reach out with a personalized message expressing your interest in mentorship and highlighting your relevant skills and goals. Social media: Follow hashtags like #womenindata and #datasciencewomen on platforms like Twitter and LinkedIn to discover mentors and opportunities.

Enquanto mulher, a melhor forma de aumentar suas chances de ser mentorada por uma mulher é fazendo conex?es apenas com mulheres. No mundo da T.I é muito fácil termos conex?es desproporcionais aqui no LinkedIn, onde a maioria das nossas conex?es é masculina. Se alguém me procurasse pedindo dicas a respeito, eu recomendaria certamente a Mulheres em dados, pois é um programa focado única e exclusivamente para mulheres. Mas se abrirmos as possibilidades em T.I temos a PrograMaria, WomakersCode e outras comunidades acessíveis aqui no LinkedIn.

I don't agree with the last part of the question. Why should men/ women be separated for such ab endeavour?? I think finding a mentor is the same for both genders.

Connecting with potential data scientists over platforms like LinkedIn might be the easiest way to expand your network. Reaching out to people with a cold email/message mentioning your goals and the support you need from them, along with telling them why they would be a perfect fit for you, is a good way to continue the conversation and probably initiate your mentorship too.

For example, LinkedIn has become a primary platform for professional networking. Individuals interested in the field of data science can connect with experienced data scientists, join relevant groups and engage in discussions. They can also participate in workshops or webinars to better understand the industry and find potential mentors. Similarly, organizations often host networking events where one can meet industry experts and share insights; a great avenue for building connections and learning from others' experiences.

We tend to find people similar to ourselves and somewhat try to spot on the common things. But sometimes, diversity shines out the similarities and enable you to fetch the best of your mentorship. Make sure to connect to people having some diverse traits and interests and this will surely help you gain better perspectives for your career.

For instance, a data scientist specializing in retail analytics might benefit from mentoring by a peer with healthcare data expertise. Such exposure can help in the application of health-data-handling protocols to retail data, ensuring improved privacy standards. Similarly, a novice programmer could learn innovative problem-solving approaches from a mentor with a graphical design background, fostering creativity. This diversity encourages a well-rounded, adaptable mindset beneficial in today's fast-paced, interconnected world.

People often like to help, but you need to be proactive about what you need. In my experience being open, respectful and curious is important, as well as taking initiative to ask for feedback.

Dedication is a key to achieving your goals and those goals might be anything that require some efforts out of us. We have to be super proactive while building our network and consider it as a primary process at and beyond the workplace. While you find your mentor, it is essential to maintain the rapport too. Hence making sure we connect with them regularly with informed updates and agendas suitable for both is prime to establishing fruitful conversations.

Uber, for instance, employs proactive measures in its ride-hailing app, where it provides riders with the estimated time of arrival and the driver's details upfront, without having to dig for that information. CRM software, such as SalesForce, also utilizes proactive strategies, like initiating reminders for salespeople to follow up on leads and calls. Businesses too, employ proactive approaches when launching marketing campaigns: they analyze consumer behavior and trends using data analytics to predict and meet consumer needs before they arise. The proactive attitude is essentially acting in anticipation, a key factor in professional growth and maintaining an edge in a competitive environment.

I strongly recommend distinguishing between coaching and mentoring relationships. In my experience, a mentor relationship is more of a pull-relationship, where the mentee reaches out to the mentor on their own, bring their problems and questions. A coaching relationship follows much more a curriculum, and has more of a push-relationship from the coach to the student, typically for a fixed set of problems or goals.

After securing a mentorship, actively develop the relationship for mutual benefit. Establish clear expectations, goals, and communication schedules with your mentor. Prepare for each session by outlining specific topics, seeking feedback, and devising actionable steps. Regularly track your progress and demonstrate your commitment to personal and professional growth. Beyond receiving guidance, reciprocate by sharing your own insights, resources, and expressing gratitude. A symbiotic mentorship dynamic fosters a collaborative and supportive environment, ensuring both mentor and mentee derive substantial value from the relationship.

Data science is a cross-functional field, so you can learn amazing things from people who are not data scientists. Software engineers can teach you how to produce high-quality, reproducible models. You can learn domain knowledge from your company veterans or functional experts and this can help you ask the right questions. Watch what your marketing experts do to learn how to clearly and concisely communicate data insights. You can learn about discovery and customer centricity from your product and UX experts. This can help you build great data products that meet your customers’ needs and drive change across your organization. Be curious about other roles and think about how you can apply these learnings to what you do.

Post you are aligned with one or mentors, try to keep pushing the boundaries and also talk about them with your mentors. Allow them to provide feedback for the work/projects you discuss with them so that you justify their efforts, time, and energy. Make sure sometimes you exceed their expectations and over-deliver so that they can gauge for you within their team/org. and you get the recognition you deserve.

With clearly defined goals in mind, it is easy to tell when goals are accomplished and a mentorship has run its course. That is not a bad thing, but both parties can move on from being actively involved to being a valuable building block in each others' extended network.

Fazer parte de comunidades de mulheres como o Mulheres em Dados certamente ajudará a encontrar uma boa mentora em ciência de dados.

Look for formal mentorship programs within organizations like the Association for Women in Science or Women Who Code. These programs are specifically designed to support women in STEM fields, offering structured and supportive environments for mentorship. How to Engage: Events and Workshops: Participate in AWIS events, workshops, and webinars to network and find potential mentors. Attend Meetups and Events: Regularly attend local WWCode events or virtual meetups to meet potential mentors. Participate in Special Interest Groups: Join groups or channels specifically focused on data science. Network Widely: Even if your direct mentor isn’t in data science, these organizations can connect you with someone who is.

Be useful When you have the identified the Mentor you need to work with. Try to think how can it be beneficial for the mentor as well to work with you. Unless, the mentor also has some leverage, the mentor would not be putting his 100 percent.

Finding a mentor in data science, regardless of gender, hinges on aligning with your personal goals and values. Decide what's crucial for you - it could be matching with your mentor on characteristics like gender, race, or language, or focusing on their knowledge and skills. Look for a mentor who possesses the expertise you seek, be it technical prowess or leadership skills. The essential factor is to find someone from whom you can learn effectively and with whom you feel comfortable and safe. This mentor-mentee relationship should be a source of growth, empowerment, and safety, tailored to your personal and professional development needs ????.