Talent Intelligence Collective Podcast - the one with Ranjan Dhar from Stratigens

The Talent Intelligence Collective Podcast 

The one with Ranjan Dhar from Stratigens


Welcome to the 27th episode of the Talent Intelligence Collective Podcast


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Alan Walker (the podcast host) describes the episode below:

Get ready to geek out over data science and talent intelligence in this meaty new episode of the Talent Intelligence Collective podcast! Regular hosts Alan Walker, Alison Ettridge and Toby Culshaw engage in an illuminating discussion with Ranjan Dhar, Principal Data Scientist at Stratigens.

Kicking things off, Toby provides a roundup of the latest TI news, spanning decentralised TI capabilities, major plays by Microsoft, SAP and others in skills intelligence platforms, early signs of cooling demand despite skill shortages, and more trends shaping the external talent landscape.

Shifting focus to our interview, we unravel Ranjan's fascinating journey into talent data science, stemming from his early days helping to scale a pioneering TI supplier from 20 to 200+ employees after its acquisition by Gartner. He recounts the challenges of working with complex, messy talent data sets, and explains typical day-to-day work ranging from data exploration to advanced machine learning modelling.

We explore a number of applied examples where Ranjan has leveraged natural language processing and other techniques to uncover insights from job postings, profiles, and more talent data sources. He emphasises how properly framing the business problem is vital before applying advanced analytics, so the techniques match the use case rather than being solutions seeking problems.

Ranjan shares thoughtful advice on working with data scientists as a business leader, highlighting the need for trust, data access, and taking an exploratory approach to the art of the possible. We discuss the pros and cons of centralised versus decentralised models for embedding TI and analytics capabilities through organisations.

With his extensive perspective spanning both the supplier side and in-house talent intelligence, Ranjan elucidates the huge potential impact when talent leaders effectively collaborate with data scientists. He demystifies how advanced analytics can transform messy, unstructured hiring data into actionable skills-based insights that drive better workforce decisions.

If you're interested in the intersection of data science and talent intelligence, don't miss this engaging insider view into the art of the possible! As always, stay intelligent folks!

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