#22 Kshira Saagar - Head of Analytics and Data Science

022_kshira.jpeg

Kshira Saagar (Shee-Raa Sa-Ga) has been with the Analytics/Decision Sciences industry for almost a decade now having worked across Americas, Asia, Europe and more importantly Australia. The bulk of his work has been focussed on developing solutions for the Digital Analytics problem spaces of the Retail, Telecom and Insurance marketing departments at some of the leading Fortune 100 clients. In his other roles, he has enabled decision making through data for clients from the Media, Healthcare, Aviation, Logistics and FMCG organisations.

He is the Head of Analytics and Data Science at The Iconic.

We speak about:

  • Why he moved from analytics consulting to building data products

  • What a data driven product should do and how to prioritise your efforts

  • How to understand your customer's problems deeply

  • How to make analytics less intimidating and more accessible

  • How to take your stakeholders on the data-driven decision making journey in next the best way (3 stages)

  • How to structure your team for maximum impact in your organisation

  • Where the product owner should sit & do

  • How to manage the high demand your team gets

  • Questions to build a great data culture in your organisation

  • Most common issues and roadblocks in creating a data driven culture and how to overcome them

  • Why the key to using data analytics in your organisation is focusing in credibility

  • How to set up a data science team from scratch and grow at hyper speed to meet demand

  • What he looks for when hiring data scientists

  • How to create and foster a team culture of continual learning - and the benefits of having one

  • How to empower the people in your organisation with data self service

  • Using lean startup principles in a corporate environment

Data Scientist job github.com/theiconic/datascientist

Kshira is based in Sydney, Australia

And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. It really helps new data scientists find us. Thank you so much, and enjoy the show!