• Data Storytelling and Practical Advice: Maggie discusses how she uses storytelling in her newsletter to inspire and support aspiring data professionals and shares a project that significantly impacted her approach.

• Impact of Volunteer Work: Maggie reflects on her roles as a WiDS Ambassador, Mentorship Organizer at Data Angels, and Social Media Manager for MeasureCamp Chicago, and the rewards of supporting young women in data science.

• Balancing Technical and User Experience: Maggie describes her work at American Express Global Business Travel on the Egencia platform, focusing on how she balances technical tasks with improving user experience and highlights a project she’s particularly proud of.

• Surprising Data Stories: Maggie shares a memorable and surprising data story, explaining how it altered people's perception of the information.

Data Angels Network: https://www.dataangels.org/home

• Use of Newsletters: Discuss how following the newsletters ‘Hiring For Tech’ and ‘Artificial Intelligence’ has influenced Riya's approach to data science projects and interview preparation.

• Returning to Microsoft: Explore Riya’s experience taking a break from Microsoft to go back to school, how it changed her perspective, and the new skills or lessons she brought back.

• Speaking Engagements: Share insights from Riya’s recent speaking engagements, including her experiences at the Women in Data Science conference and the Olympic Data Party, and how these events contributed to the open-source community.

• Research Impact: Insights into Vaibhava's research on knowledge graphs, machine intelligence, IoT, and stock price forecasting, including challenges and rewards in transforming research into publications.

• Community Engagement: Experiences and impact of roles as an ambassador for Women in Data Science, Pie and AI, and Adobe, and strategies for balancing tech education promotion with community connections.

• Integration of Skills: How diverse coursework in machine learning, NLP, data manipulation, and time series analysis is applied to current projects and research, and the influence of specific courses or concepts on problem-solving.

• Internship Experience: How various internships in AI and data science have shaped Vaibhava's problem-solving approach and the balance between learning from different environments and contributing effectively to projects.

• LinkedIn Success: Strategies for gaining a large following and becoming a top AI voice on LinkedIn.

• Computational Humor and Context: Role of context in pun interpretation by language models and the impact of language ambiguity on pun recognition.

• Irony Detection in Tweets: Distinguishing types of irony (e.g., sarcasm) in tweets and the challenges of detecting irony in short, informal texts.

• AI in Enterprise Solutions: Evolution of AI and Machine Learning roles in enterprise solutions over the years based on Madiha's career progression.

• Inclusive Learning Environments: Influence of experiences in student support roles on creating inclusive learning environments in technical fields.

In celebration of International Women's Day, this special episode brings together influential women leading the charge in Data Science and AI. Hosted by WiDS TT and WiDS San Jose Youth, join us for a compelling fireside chat featuring women trailblazers sharing their insights on navigating and excelling in these dynamic fields.

Tune in as our guests discuss:

- actionable strategies for breaking into Data Science and AI

- explore valuable resources like mentorship programs

- online courses and communities

- reflect on the personal pillars of resilience, adaptability, and continuous learning that have shaped their journeys.

This episode is designed to inspire and empower aspiring data professionals, offering them the tools and confidence needed to thrive in these transformative industries.

• Inclusion Impact: A story of how Malvika’s efforts in promoting inclusion made a difference, and trends or innovations in urban data systems likely to impact city planning and development.

• ChatGPT in Data Analysis: Techniques for using ChatGPT to summarize large datasets or lengthy text, common pitfalls, and the limitations of LLMs in transforming data formats.

• Leadership Development: Influence of past leadership roles (football captain, event coordinator) on Malvika’s approach to leading projects at Carnegie Mellon and in her current role.

• Staying Updated in AI: How Malvika keeps up with AI developments, incorporates insights into podcast discussions, and future AI topics of interest, particularly in areas intersecting with human experiences like dating.

AI is Not Taking Your Job podcast: https://open.spotify.com/show/1qUPErphWKUg16rsVko9PP?si=ba768ac0248f4eed

• Diverse Background and Leadership: Impact of university roles and extracurricular activities on managing technical projects.

• Engaging Different Age Groups: Tailoring complex STEM ideas for various audiences, combining experiences as a team manager and council member.

• Women in STEM Podcast: Inspiration behind the podcast, evolution of the vision, and surprising insights from high-profile interviews.

• Challenges in Digital Solutions: Experiences optimizing Tanzu Kubernetes solutions for scalability and reliability at VMware.

Women in STEM podcast: https://open.spotify.com/show/4pJNT1DLx3EddXfnVuisEj?si=202c8362400a4aee

Transition from Corporate to Academic Setting: Navigating the shift from Wells Fargo to Cornell and the transferable skills.

Diverse Data Projects: Insights from analyzing data in mental health, gaming, and accessibility, and lessons learned.

Writing for Reinvented Magazine: Trending tech topics and their influence on marketing data analysis at Cornell.

STEM Education Impact: Lydia's experience as an MIT instructor in Barcelona. The transformative power of STEM education in communities. Advice for young women exploring tech and data science.

Interdisciplinary Research: Lydia’s research on the connection between music, animals, and human well-being. Encouragement for high school students to explore interdisciplinary research.

ML Summer Analyst Success: Lydia’s approach to saving 1,000 hours and increasing bids by $100 million. Key skills and mindset for making a significant impact.

Data Science in Industry: Transition from IBM to Visa and how previous projects in automotive and supply chain influence her work in fraud detection at Visa.

WinSci Pakistan: https://instagram.com/winsci.pak?igshid=YmMyMTA2M2Y=