Share QuantumBlack Voices
Share to email
Share to Facebook
Share to X
By QuantumBlack
5
44 ratings
The podcast currently has 10 episodes available.
See www.mckinsey.com/privacy-policy for privacy information
See www.mckinsey.com/privacy-policy for privacy information
We then do a deep-dive on the topic of fairness, and why every data scientist has a responsibility to identify and mitigate societal bias found in historical data. Viktoriia is also incredibly passionate about promoting the representation of women in data science and STEM industries, and we talk about the work she and QuantumBlack are doing to improve that representation.
See www.mckinsey.com/privacy-policy for privacy information
We do a deep-dive on the product Virjinia is building in QuantumBlack Labs, and discuss how OKRs keep our teams on track in a highly autonomous environment. Virjinia has aspirations to build her own company, and explains why the culture in QuantumBlack Labs and the support of McKinsey & Company creates a perfect testing ground for her to grow as a product manager.
See www.mckinsey.com/privacy-policy for privacy information
Philip's belief is that "machine learning is eating the world". This might sound a little scary at first, but further reinforces why we need practitioners like Philip who can unpack this complex discipline, and shine a light on both its potential impact, as well as its limitations. Philip also gives us a deep dive on a real-world machine learning use case, and leverages this example to explain core concepts like causation and model deployment at scale.
See www.mckinsey.com/privacy-policy for privacy information
See www.mckinsey.com/privacy-policy for privacy information
We talk about the importance of inner sourcing, and how to scale technical assets like code as a reusable knowledge resource. Thomas also explains the importance of end-users when creating AI solutions - and how empathy for their role and needs is essential to ensuring the adoption of advanced analytics within an organization.
See www.mckinsey.com/privacy-policy for privacy information
We talk about the importance of monitoring model performance when trying to predict house prices, and why a continual improvement mindset is important to maintain a diverse and inclusive working environment.
See www.mckinsey.com/privacy-policy for privacy information
We talk about why experimentation and iteration are critical to building successful products - and we discuss the amplified value that can be gleaned from ensuring everyone is involved in creative problem solving - regardless of discipline.
See www.mckinsey.com/privacy-policy for privacy information
We talk about her background in engineering. Her evolution into a product manager. And how her team's ultimate aim is to ensure their end-users have no reason not to use their product.
See www.mckinsey.com/privacy-policy for privacy information
The podcast currently has 10 episodes available.