Career advice, learning, and featuring women in ML and AI - Isabella Bicalho
Dec 13, 2024
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In this engaging conversation, Isabella Bicalho, a Machine Learning Engineer and passionate advocate for women in data science, shares her journey from academia to freelancing in AI. She discusses the vibrant AI scene in France, her experiences with open-source contributions, and the significance of mentorship. Isabella reveals her insights on balancing technical and soft skills, the pros and cons of freelancing vs. full-time work, and highlights her mission to showcase women's achievements in the tech field through her newsletter.
Isabella Bicalho's career transition highlights the importance of leveraging interdisciplinary skills from biology and computer science in machine learning.
Her experience with freelancing emphasizes the benefits of flexibility and diverse project exposure while overcoming initial client acquisition challenges.
Through her Substack newsletter, she actively promotes women's accomplishments in data science, fostering a supportive community and inspiring future generations.
Deep dives
Isabella's Journey into Data Science
Isabella began her career with a background in biological science, initially aiming to become a bioinformatician. She was fortunate to study at a university that allowed her to take computer science courses, where she developed crucial programming skills. As she pursued her master's in bioinformatics, her fascination with machine learning grew, particularly as it gained prominence during her studies. This unexpected pivot led her to embrace machine learning fully, transforming her career path and allowing her to explore her passion for data.
Transitioning to Freelancing
After a stint in research that wasn't fulfilling, Isabella decided to pursue freelancing as a machine learning engineer. She was drawn to the flexibility and variety that freelancing offered, liking the chance to work on different projects across various companies. Initially cautious about the challenges of finding clients, she quickly discovered that the skills she honed during her previous experiences positioned her well in the market. Through determination and proactive networking, she secured her first freelance job shortly after transitioning.
Value of Open Source Projects
Isabella highlighted the critical role that open source contributions played in her professional development. Engaging in open source allowed her to collaborate with motivated individuals and tackle real-world problems, enhancing her skills and expanding her network. She contributed to community-based projects, including the Hugging Face computer vision community course, which facilitated connections with others in the field. These experiences not only bolstered her technical capabilities but also offered significant insights into teamwork and project dynamics.
Empowering Women in Data
Through her Substack publication, DataLike, Isabella actively promotes the achievements of women in the data science field. The newsletter features interviews with female data professionals, sharing their unique journeys, challenges, and insights. This initiative arose from her desire to create a supportive community that amplifies women's voices and experiences in data-related careers. By highlighting these stories, she aims to inspire others and broaden the narrative surrounding women's contributions to data science.
The Importance of Networking
Isabella underscored the significance of networking in her career advancement, noting that many opportunities arose from connections she made in various communities. By engaging with fellow data enthusiasts and professionals, she discovered job openings, project collaborations, and mentorship possibilities. She emphasized that effective networking often occurs naturally within passionate communities, making it easier for individuals to reach out and form valuable connections. This collaborative environment encouraged her and others to take risks, seek advice, and expand their professional horizons.
In this podcast episode, we talked with Isabella Bicalho about Career advice, learning, and featuring women in ML and AI.
About the Speaker:
Isabella is a Machine Learning Engineer and Data Scientist with three years of hands-on AI development experience. She draws upon her early computational research expertise to develop ML solutions. While contributing to open-source projects, she runs a newsletter dedicated to showcasing women's accomplishments in data science.
During this event, the guest discussed her transition into machine learning, her freelance work in AI, and the growing AI scene in France. She shared insights on freelancing versus full-time work, the value of open-source contributions, and developing both technical and soft skills. The conversation also covered career advice, mentorship, and her Substack series on women in data science, emphasizing leadership, motivation, and career opportunities in tech.
0:00 Introduction
1:23 Background of Isabella Bicalho
2:02 Transition to machine learning
4:03 Study and work experience
5:00 Living in France and language learning
6:03 Internship experience
8:45 Focus areas of Inria
9:37 AI development in France
10:37 Current freelance work
11:03 Freelancing in machine learning
13:31 Moving from research to freelancing
14:03 Freelance vs. full-time data science
17:00 Finding first freelance client
18:00 Involvement in open-source projects
20:17 Passion for open-source and teamwork
23:52 Starting new projects
25:03 Community project experience
26:02 Teaching and learning
29:04 Contributing to open-source projects
32:05 Open-source tools vs. projects
33:32 Importance of community-driven projects
34:03 Learning resources
36:07 Green space segmentation project
39:02 Developing technical and soft skills
40:31 Gaining insights from industry experts
41:15 Understanding data science roles
41:31 Project challenges and team dynamics
42:05 Turnover in open-source projects
43:05 Managing expectations in open-source work
44:50 Mentorship in projects
46:17 Role of AI tools in learning
47:59 Overcoming learning challenges
48:52 Discussion on substack
49:01 Interview series on women in data
50:15 Insights from women in data science
51:20 Impactful stories from substack
53:01 Leadership challenges in projects
54:19 Career advice and opportunities
56:07 Motivating others to step out of comfort zone
57:06 Contacting for substack story sharing
58:00 Closing remarks and connections