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Top 7 Expert Advice From Women Data Scientists

Top 7 Expert Advice From Women Data Scientists

Top-7-Expert-Advice-From-Women-Data-Scientists

The Rising’, an event hosted by Analytics India Magazine, has been the biggest conference for women data science leaders and women professionals from across the domain. With the second edition coming up in Bengaluru — Hotel Radisson Blu on March 20th, 2020, the event is aimed towards promoting and celebrating women innovators in data science. The conference is also going to highlight the career achievements of women data science leaders and executives.

In this article, we are going to list down, in no particular order, top 7 expert tips from women data scientists from The Rising 2019.

How To Start Your Career In Data Science?

As a data scientist, one needs to have a lot of patience – Mathangi Sri, Head of Data at Gojek.

In this talk, Mathangi Sri, head of data at Gojek, spoke about her 15 years of journey in the field of data science and the learning acquired. She also discussed her experiences working across multiple problems and various types of data and the challenges she witnessed over the years. One crucial advice she mentioned in the talk was to have enough patience. She said how it is easy to build a model sitting behind the desk, but it takes an ample amount of time to make it to a production level from an engineering standpoint. So, she advises young data scientists to have a lot of patience. She said, “Data scientists would need a lot of patience to get the data, as well as, would need a lot of patience to wait for these models to go live.”

Reskilling is of utmost importance in the digital era – Sohini Mehta, Global Service Delivery Head of Analytics at Wipro

Sohini Mehta, the global service delivery head of analytics at Wipro, in the talk, spoke about the importance of reskilling in this digital era. Considering the dynamic landscape of technology, which is evolving every day, it has become imperative for organisations to provide reskilling/upskilling opportunities for employees to improve the talent workforce. Reskilling will not only bridge the talent gap but will also offer opportunities for employees to learn and be relevant in the world of data and analytics. She strongly believes in reskilling over hiring a new individual, where the existing employees are taught newer skills. In this process, organisations are not only building a talent pipeline but also improving employee retention to a great extent. 

To remove biases in machine learning, humans need to increase diversity – Smitha Ganesh, Principal Data Scientist at ThoughtWorks

Smitha Ganesh is the principal consultant and data scientist at Thoughtworks, and in this talk, she spoke about how human biases impact AI technology. She believes that biases and prejudices are common elements wherever there is a system that encompasses humans, which is something very inherent. But when this inherence gets into the building an algorithm, these effects get compounded with time. And that’s why it is crucial to fight prejudice in AI. To remove these biases, according to Ganesh, humans need to incorporate a diverse mindset for data collection, which will help in building and taking AI to an elevated level and recognising the vitality involved with AI training systems.

Drive towards a cleaner future through data – Deepika Sandeep, Practice Head – AI & ML at Bharat Light & Power

Deepika Sandeep is the head of AI and ML at BLP Clean Energy, and in this, thought-provoking talk she spoke about how organisations can use newer technologies like AI, ML and augmented analytics for creating a better future. She suggested how AI and ML can benefit industries creating renewable energy, reducing downtime in the utility sector, managing energy, bringing about automation, and optimising inventory. She strongly believes in using AI and ML to drive a push towards a cleaner future with the help of data.

We need more women in AI – Vaishali Kasturae, India head of ISV Business Segment at AWS

Vaishali Kasturae, the India head of ISV Business Segment of AWS, discussed the urgent need for more women in the world of AI. This need is not only to empower more women in AI but actually to make AI safer and bring in a diverse perspective to make sure that people are using AI the way they should. She mentioned that organisations must ensure that their AI systems do not discriminate inappropriately against any individual or group.

However, if the technology is always built by only certain groups of people, then the chances of involving discrimination will increase, even if it is not intentional. Kasture believes that the best way for combating sexism is to have a diverse data science team. She said, “If we need to make AI safe in the future it is important to have a blue tick mark for approved AI models, as we have on our social media for verified accounts, only this time women should give the verification.”

AI should be used for noble causes, which can help in saving lives – Geetha Manjunath, Co-founder and CEO of NIRAMAI

Dr Geetha Manjunath is the founder, CEO and CTO of NIRAMAI, and in this talk, she spoke about the noble solution developed by NIRAMAI to detect early-stage breast cancer in a non-invasive manner. The talk focuses on how AI can be used for such a noble cause which is helping several women of the country to have early detection of breast cancer, which, in turn, will save their lives. In a country like India, where there is a massive increase in the incidences of breast cancer, Niramai is using artificial intelligence, machine learning algorithms, big data analytics to improve breast cancer diagnosis. And similar to the name NIRAMAI, which means ‘being healthy’ Geetha Manjunath also strongly believes in using emerging technology in making everyone healthy in our country.

Organisations should enhance employee satisfaction using AI – Dr Shivani Rai Gupta, head of AI & data science at Capgemini

Dr Shivani Rai Gupta is the head of AI and data science in Capgemini, and in this talk, she spoke about how organisations are focused about creating newer technology and products for their customers but rarely utilises the same for insiders to engage employees and increase their satisfaction level. She firmly believes that if employees are engaged then the overall productivity of the business increases. She mentioned that if the technical difficulties and operational challenges are reduced for employees, their satisfaction level increases. According to her, the four ways AI can help employee satisfaction are — introducing AI chatbots to improve onboarding experience; applying AI to capture employees’ daily experiences in real time; introducing AI to enhance team collaboration; using AI to enable timely learning and development to keep the employees engaged.

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