We can't keep qualified data scientists/analysts at our company.

Posted by Chisel Analytics on Feb 13, 2020 6:45:00 AM

Your hiring manager tells you that another data scientist quit, and it leaves you scratching your head as to why you cannot keep qualified data scientists at your company.

With the tight data science talent market, the demand for analysts outstrips the supply. This increases the pressure to retain your existing data team. While you may not be able to control everything once someone starts in the job, here are some things you can do before they start.

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Topics: Recruiting Data Scientists, Competitive Edge

We're not seeing the results we thought we would. What did we miss?

Posted by Chisel Analytics on Jan 30, 2020 6:45:00 AM

The advanced analytics space is all about results. Your company expects the data team you built to deliver actionable insights that improve the company. However, when that same team fails to achieve the desired results, you get the brunt of the blame.

The market for data science talent is tight, and it doesn’t give you much range to find top talent. Sometimes it seems like finding qualified analytics professionals is like looking for a needle in a haystack. Even when you think you have hired the right person, you are left scratching your head when that person turns out to be a bad hire. You ask yourself, "what am I missing? What do I need to change?"

Here are some things to think about during your next data talent recruitment.

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Topics: Recruiting Data Scientists, Skillset of Data Analysts, Innovation, Competitive Edge

We aren't meeting current expectations. How do we change that?

Posted by Chisel Analytics on Jan 16, 2020 8:38:00 PM

Another day comes to an end with the hiring manager telling you that a new hire isn't meeting expectations. New hires who don't work out not only break the trust in the recruitment process but cost the business money. For small businesses, the cost of a wrong hire could reach $8,000 and up to $240,000 for larger firms. These numbers exclude the costs of reduced productivity, brand damage, reduced employee engagement, and increased time managers spend mitigating poor performance and finding replacements.

As a recruiter, you depend on the information the hiring manager gives you to prepare a job posting and find the right candidates. Plus, you discover that your range of qualified candidates is small. Without having a technical background, and using a small sample size for reference, it can be a challenge for you to discover why the previous hires turned out to be bad hires.

You might think that an Applicant Tracking System (ATS) could help broaden your scope of data talent acquisition. However, you will be surprised to find out that ATS will not help you. Here’s why.

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Topics: Recruiting Data Scientists

Top Jobs for Data and Analytics Professionals

Posted by Chisel Analytics on Jan 3, 2020 6:45:00 AM

An Expansion of Analytics-focused Role

In response to the huge growth in data and its increasing importance to organizational strategy and growth, a variety of roles have been created to manage and support organizational efforts. This has created a growing set of opportunities for analytics professionals to build a career focused on data, strategy and analytics.

These roles run the spectrum of needs, from data engineers responsible for database design and data acquisition, to data scientists focused on exploring captured information and deriving insights, and business analysts and analytics managers leveraging data to monitor organizational performance.

These roles – in particular data scientists – enjoy some of the most competitive compensation and widest array of opportunities for new professionals.

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Topics: Recruiting Data Scientists, Skillset of Data Analysts, Innovation, Competitive Edge

It takes too long to find quality data scientists.

Posted by Chisel Analytics on Jan 2, 2020 9:02:00 PM

Has the range of your data scientist talent search shrunk to the point that it takes too long for you to find quality analytics professionals? Nowadays, this is common because the demand for these professionals is outstripping the supply.

Quality data professionals possess an array of technical and analytical skills that are in high demand. However, the overall pool of these professionals contains a small number of qualified candidates. You might bring in a large number of candidates to interview with your hiring manager. However, they tell you that the candidate did not fit the scope of skills for which the company is looking.

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Topics: Recruiting Data Scientists

The folks we have hired haven't been as strong as we were hoping for. How can we improve recruiting for competency?

Posted by Chisel Analytics on Dec 19, 2019 2:05:00 PM

As a recruiter, you dread this situation: After the first month on the job, the new hire turns out not to be the strong candidate they exhibited in the talent acquisition process. You hope that, perhaps, they only need additional time to adjust. Still, when the hiring manager tells you that the new hire doesn't seem competent for the role, your stomach drops.

Indeed, something went wrong. Like with other positions you recruit for, you work with the information the hiring manager gives you - what are the required skills and experience, what is the budget, where the person will work, and to whom they will report. You depend on what the hiring manager tells you and prepare a job posting from this input. When it comes to data analytics roles, however, without having a background in the field itself, it is a challenge for most recruiters and HR departments to discover why the people you hire turn out not to be strong in the competencies required for the job.

In the data specialist space, two types of bad hires sneak through. First, some hires end up not having the skills they claimed to have during the hiring process.

And second, there are the new hires who were hired based on a poor job description, which originated with the information provided by the hiring manager.

Addressing these two concerns can help you improve recruiting for and, more importantly, hiring for competence.

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Topics: Recruiting Data Scientists, Skillset of Data Analysts

We aren't meeting current expectations. How do we change that?

Posted by Chisel Analytics on Nov 25, 2019 6:45:00 AM

The hiring manager tells you, “Another new hire isn’t meeting expectations.” New hires who don’t pan out not only foil the trust in the recruitment process but costs the business money. If you work for a small business, the cost of a poor hire could reach $8,000, and up to $240,000 for larger firms. These numbers do not include the costs of reduced productivity, damaged brand, decreased employee engagement, and increased management time spent on fixing under performance.

As a Recruiter, you work with the information you are given - what are the required skills and experience needed, what is the budget, where the person would be working and to whom they would report. You depend upon what the hiring manger tells you and have to prepare a job posting from this input. Without having a technical background, it is a challenge to discover why the previous hires weren't considered good hires.

But do you realize that there's an additional reason why your job is so hard?

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Topics: Recruiting Data Scientists, Skillset of Data Analysts

Hiring managers' job descriptions are so technical

Posted by Chisel Analytics on Nov 21, 2019 6:45:00 AM

Hiring managers' job descriptions are so technical, it's hard to feel confident in finding good candidates. Help.

Job descriptions for analytics specialists are ever evolving and can seem inaccessible. Consequently, the specs for the needed work become a bottle neck in your way of recruiting the right data or analytics candidate. The way the hiring manager wrote the job posting puts you in a tight spot. You know it should be modified, but without being a data scientist yourself, what can you change without attracting the wrong candidate or delaying the process. Also, you lose confidence in your ability to find the right person. Here are some tips to help you translate your hiring manager's requirements.

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Topics: Recruiting Data Scientists, Skillset of Data Analysts

We can't find qualified data science candidates

Posted by Chisel Analytics on Nov 7, 2019 6:45:00 AM

Yes, your company is having a hard time hiring qualified data scientists, and there are two reasons why.

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Topics: Recruiting Data Scientists, Skillset of Data Analysts

People in other departments can't get the data analytics they need

Posted by Chisel Analytics on Oct 24, 2019 6:45:00 AM

When departments can't get the data analytics support they need, it can hinder progress for your company and risk your competitive edge. This lack of support can arise when people in other departments don’t know what types of data support they need. As a result, the recruiters who support them can’t recruit data scientists for the right roles or have to find qualified talent in a short time.

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Topics: Recruiting Data Scientists, Scope of Work

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