Discover Your Next Data Science Leader
by Sonia Di Carlo
Senior Partner, Talent 5th Jan 2017
Sonia is a Senior Partner at Avellio. She is responsible for the Insight and Analytics team in the retail sector and has developed talent acquisition partnerships with over 60 leading FTSE 350 companies.
Establishing a data science team can be a significant investment for any company. Many data rich companies now understand the importance of hiring data scientists to help them gather further insights that enable them to make better commercial decisions and to remain competitive. But building a data analytics team poses a unique set of challenges of its own. Whist more professionals are joining the data science talent pool, good analysts and solid data scientists are difficult to come by.
1. Hiring a chief data scientist?
For companies seeking to secure and appoint a head data scientist to develop commercial capability, when selecting and appointing a leader be sure to qualify their aptitude to engage and counsel the executive team, it helps to look beyond the technical skills.
The lead data scientist that you ultimately appoint should be both technically competent and have the people management skills necessary to successfully engage the in situ data analytics team, before further working to build it out. In addition they should also be a key agent for change within the wider company, working cross functionally, with the ability to communicate opportunity and rationalisation based on the what the business data is telling them.
2. Its a data scientist-led market, what makes you attractive and separates you from Google?
Data scientists that are active in the market and seeking their next career opportunity receive many enticing offers from big brand names and highly innovative companies, consider what you have to offer thats truly unique and special and how you will push the message.
Top performing data scientists with a strong suite of technical and commercial skills are pitched to by company talent scouts and agency recruiters daily, and will likely be presented with multiple opportunities to consider. Before connecting and 'pitching' your business to any professional take a look at their visible track record, isolate their strengths, and then connect that with how you would engage them on projects and challenge them to perform their best work yet, whilst further considering what additional aspects of your opportunity are likely to be truly alluring, from the aspect of salary, to the cutting edge technologies and methodologies employed within the business.
3. Design some flexibility in to your hiring brief.
Considering the scarcity of talent and high salaries, you will likely be demanding with your brief for a data scientist, but beware of pricing yourself out of the market with your wish list.
Time and again businesses are held back by their rigidity on hiring briefs, its crucial that those involved on hiring are open to compromise on the full suite of skills and experience requirements for the role. This consideration is especially important when seeking to hire in data scientists with niche domain experience. By designing some flexibility in to the brief it will afford you a wider selection of talent, which although may be a little short on industry experience, have the aptitude to be up-skilled and schooled on the nuances of your business and the wider industry space that you operate in.
4. How will you position the role of 'chief data scientist' within the business?
It is important that data scientists know their work is valued, so carefully consider your reporting structure. Experienced senior data scientists need a clear channel and a peer level position with the executive team, they are delivering real business value through actionable insights, and therefore do not want to get lost in the role of the wider IT business unit.
By structuring the role of Chief Data Scientist as a position that 'sits on the right hand side of the Chief Executive', this provides a clear message to contenders for the role that data science is absolutely an important executive level role. We often see lead data scientists tagged on to the IT or marketing business units, sandwiched somewhere between BI and data warehousing. Depending on the structure an hierarchy of your business, if you fail to position the Chief Data Scientist role as a pivotal position, this will present real challenges during the selection and hiring process.
5. Make a commitment to improving the quality of data within the business and apportion a budget for it from your marketing spend.
Investment in the latest tools and technologies is crucial as it illustrates a commitment to data initiatives and guarantees successful outcomes for the incoming lead data scientist.
Whilst most predictive analytics professionals will want to see a company investing significantly in the latest technology, data scientists in particular will expect to have both the budget and authority to select and implement new progressive technologies on demand, to enable them to best perform their function.
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