How can you navigate a non-linear career path in the tech industry? In this podcast, Kaboo Founder Neha Shah meets with Atlassian Data Science Lead Nisha Iyer to discuss non-linear career paths, the power of continuous learning, and the significance of product-market fit. Gain valuable insights on leveraging user interviews, synthesizing data, and understanding customer needs.
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Show Notes
- Nisha Iyer reached out to people in the field and secured a data scientist position at the FDA.
- Moreover, Nisha’s FDA experience allowed her to practically apply academic knowledge and recognize the need for advanced data science techniques.
- The guest at Discovery Communications transitioned to a data scientist role and faced imposter syndrome while coding.
- Additionally, non-linear career paths often reward individuals.
- Python highlights itself as a powerful programming language that unlocks opportunities in various fields, including journalism.
- The podcast showcases Nisha’s journey from communications and the restaurant industry to becoming a data scientist in tech.
- Furthermore, navigating a non-linear career path values perseverance, self-advocacy, and continuous learning.
- The discussion focuses on the importance of continuous learning and curiosity in product management or leadership roles.
- The discussion encourages individuals to seize opportunities and take risks in fields without established job titles.
- Share lessons learned from failures and emphasize the importance of market research and understanding user needs.
- Discuss the role of UX in product design and the challenges product managers face in conducting user interviews.
- CoNote is an AI tool that synthesizes user interview findings to provide automated and unbiased insights.
- Find valuable knowledge and insights in various channels within an organization, such as customer support calls and sales interactions.
- Combine different research methods, like UX research and market research, to gain valuable insights.
- Listen to users and iterate accordingly, as user acceptance and feedback are crucial in determining product market fit.
- Mention the importance of balancing engineering planning with iteration and avoiding the sunk cost fallacy.
- Emphasize diversity and representation in building effective teams, acknowledging the importance of different backgrounds and experiences.
- Leaders should be mindful of biases and strive for inclusivity in hiring and team formation.
- Suggest strategies for finding mentors, including cold messaging professionals on platforms like LinkedIn and utilizing mentorship platforms.
- Lastly, make the most of mentorship relationships by aligning goals with the mentor’s expertise and preparing specific questions.
About the speaker
I am an innovator and a leader. My passion is applying ML and AI to industry problems and thinking through engineering and productizing these solutions at scale, and as products. I can drill down to the technical details and bridge the communication between tech and business. I love building teams and helping people grow and flourish in their careers. While at Data Society, I built my team from the ground up, from hire 2 to a 40+ person team. I led the technical side of the company which consisted of data scientists, ML engineers, software engineers, UX/UI Designers and technical product managers.
About the host
My experience covers the trifecta of B2B Product Management, Sales, and Marketing. I also co-founded a B2C startup focused on family and education technology. I believe technology can be a creative and powerful driving force for change, and am passionate about building products that improve every day experiences.