Dina Bavli & Maya Malamud

Independent Pathways in Data Science: Challenges and Opportunities for Freelancers
Maya Malamud

Bio

Dina Bavli has 5+ years of experience in data science, specializing in NLP, Speech Recognition, and Event Prediction. Her thesis focused on Persuasion Classification and has also contributed to a research project at the German Aerospace Data Science Center. Dina is an active data science lecturer, contributing to conferences in Israel and abroad. She writes technology articles and mentors others, emphasizing the importance of knowledge exchange and growth. Motivated by a community member’s transition to freelancing, Dina decided to explore the freelance data science realm. She aims to leverage her extensive knowledge and network to gather and share insights on freelancing in data science.

Maya is a Senior Data Scientist and Researcher at Timna (Ministry of Health) and a Data Science freelance consultant, mentoring Data Science projects at Y-Data and teaching as part of the Biomedical Data Science course at the Hebrew University Business School Executive Education. With experience in large companies as well as startups in various industries and academia, from NLP to Healthcare, Maya developed projects via all stages of data pipelines, from ideation to research and production-level products. Maya holds an M.Sc. in Applied Statistics and a B.Sc. in Industrial Engineering and Management from Ben-Gurion University of the Negev. Maya also mentors individual aspiring data scientists in their career journey and volunteers in WiDS and Baot. When she isn’t creating models to make the world a better place, she writes poetry and plans trips around the world with her family.

Abstract

Ever wondered why so few data scientists seem to go in the independent direction and yet we hear such amazing success stories from those who did? Can anyone embark on this journey? What will it take of you, besides being a great experienced professional? And will the challenges be different for women vs men?

In this thought-provoking roundtable, we’ll answer these questions and offer insights for aspiring freelancers and strategies for organizations to collaborate with these talented individuals. We’ll explore the evolving role of freelancers in data science, addressing the question of how these professionals navigate challenges such as staying abreast of technological advancements and managing the entrepreneurial aspects of their careers. We’ll discuss what unique pros and cons this career path entails and what the undeniable benefits are of companies hiring in that format.

Join us as we unravel the complexities and opportunities within the world of independent pathways in data science.

Planned
Agenda

8:45 Reception
9:30 Opening remarks by WiDS TLV ambassadors Noah Eyal Altman, Or Basson, and Nitzan Gado
9:45 Dr. Aya Soffer, IBM: "Putting Generative AI to Work: What Have We Learned So Far?"
10:15 Prof. Reut Tsarfaty, Bar-llan University: "Will Hebrew Speakers Be Able to Use Generative AI in Their Native Tongue?"
10:45 Break
11:00 Lightning talks
12:20 Lunch & poster session
13:20 Roundtable session & poster session
14:05 Roundtable closing
14:20 Break
14:30 Dr. Orna Amir & Hila Kantor, Google: "A User-Centric Framework for Quantifying Notification Harm"
14:50 Naomi Ken Korem, Lightricks: "Mastering the Art of Generative Models: Training and Controlling Text-to-Video Models"
15:10 Dr. Yael Mathov, Intuit: "Surviving the AI-pocalypse: Your Guide to LLM Security"
15:30 Closing remarks
15:40 The end