Data and Analytics Leaders: Stand Out in a Crowded Job Market

The Data Job Market is Strong, and it has been for the past few months (at the time of this article's publication).

And to be honest, it's only projected to grow, with roles becoming increasingly complex with emerging tech.

But this promise also brings a lot of competition.

This problem is further compounded by the large number of "Aspirational" job seekers in addition to the already crowded "immediate" job seekers.

btw, here's what I mean by the above terms:

Immediate: Actively looking. Laid off, or otherwise want to make an immediate change.

Aspirational: Already employed but Passively looking. Open to interview if the right opportunity knocks.

According to TopResume’s survey, at any given time ~70% of people(who are already employed) are open to new opportunities

We talk to thousands of IT leaders every year, and we can confirm this finding. It's rampant.

And that's what brings about a significant amount of competition.

How significant?

Here are the number of Data and Analytics leaders in the US

At Sr. Manager/Director Level: 190k+ folks in the United States

At VP Level: 68k+ Members

Mind you; these are just up to my 3rd-degree connections, not everyone. The actual numbers will be way more than that.

If you think that not all of these folks would be qualified for the roles you are applying to, you are absolutely right.

But that doesn't keep them from drowning you out in the noise.

The Big Mistake...

If I had a dollar for every time a Data Leader told me, "Well, Data is just Data. If I can do X here, I can do Y there..."

...I could retire this year. (JK, not really, with how bad inflation is)

But in all seriousness, Data isn't just data.

And don't get me wrong, I am no Data Expert.

I say this simply by observing hiring patterns over thousands of jobs we have shot for this year and hundreds of interviews we have landed for senior leadership roles in the data field.

Most executives position themselves as "I am a Data Strategist." They put forth a catch-all narrative:

• On their resumes
• Their LinkedIn profile
• In Interview introductions
• On Networking messages

Thinking that if they cast a wide enough net, they would catch something.

However, the problem is that hiring companies look for specifics.

With so much talent available in the market, they can literally cherry-pick who they want to interview.

Thus, the strategy to win this game isn't to put forth a catch-all narrative but instead to niche down.

We analyzed thousands of job descriptions at the Senior Leadership level to develop a system for reliably positioning oneself in a narrow market.

And I will present a finding towards the end that will shock you- for the better.

You would benefit greatly if you slice and dice your experience along these lines:

#1 What Data Discipline Are you primarily an expert at

These could be:

• Data Engineering
• Data Science and Analytics
• Reporting and BI
• Data Management and Governance
• Data Architecture

As obvious as these sound, many people don't make them evident in their marketing. When a recruiter has a few seconds to discern whether you are a fit among thousands of other applicants, this comes into play significantly.

Besides, if you were heavily involved in the Data Platform building side of the house, they might not consider you for roles that involve a heavy focus on predictive analytics model development.

Remember: At the senior leadership level, they don't hire you so YOU can grow. They hire you so you can GROW the business. They want you for the skills and expertise you already have.

#2 What Key Effort have you primarily driven

• Was it Modernizing a Data Platform or moving the data domains to a cloud-based data platform?
• Perhaps you established an in-house Data Science practice.
• Maybe you were the catalyst for driving data use and enabling data-driven decision-making across the organization.
• Or your most recent effort involved rearchitecting a data platform.
• You could be involved in implementing MDM initiatives.

You get the idea. In your recent past, you perhaps have driven a significant change in your Data Org.

Think to yourself, what was that specifically?

How did it help the organization?

Presenting these initiatives with key results will help recruiters and hiring managers identify you better for their specific cases.

#3 What function of the business did you help with?

A few examples could be:

• Improved Marketing Analytics: Maybe you are an expert at Media Mix Modeling, Customer Retention, Marketing Attribution, Experimentation
• Supply Chain: Implemented Demand Forecasting, Inventory Optimization
• Sales: Customer segmentation, Churn Prediction models.
• Customer Service: Implemented AI Chatbots, Put in call volume prediction engine.
• HR Analytics: Built Self-serve analytics for HR Reporting

You can see how each of these function-specific

These use cases are important in understanding your domain expertise. The higher up the ladder you go, the more business-focused your role becomes.

At that point, if you can clearly call out your domain expertise, it gives a hiring manager a subconscious vote of confidence that you are the right kind of candidate.

In continuation to the domain expertise, another thing to consider is:

#4 What Industry are you most familiar with?

Different industries have their own differing complexities in how they handle their data. And because of this, they often look for industry-specific experience.

Again, it feeds into the idea that Senior Technology Leaders ARE Business Leaders.

A few examples of how nuances of Data challenges differ by industry are:

• Healthcare: Challenges include Data Privacy and PII, Security, regulatory compliances (HIPAA and HITRUST), integrating data from disparate systems, and interoperability.
• Financial: Regulatory compliance and High transaction Data volume. Familiarity with Fraud and Risk detection models, and preparing data for the same.
• Manufacturing: Supply Chain Complexity, Predictive maintenance type use cases.
• Telecom: Network Data Analysis, Predicting Call Volumes, Customer Support
• Retail: Setting up a Customer Data Platform, Marketing Analytics, Supply Chain optimizations, Pricing and recommendation systems.

Thus, if someone can identify the industry you're coming from and/or you apply to roles in the industries you have expertise in, you'd have a much higher negotiating leverage.

And lastly, think of where you stand in terms of

#5 The Level of Maturity of the Data Org

Different companies operate at different stages of their data journey.

Some are in their initial stages, getting their data in one place, clean, and organized to start data-driven decision-making across the organization.

Some improving the quality of their analytical models, and exploring new areas for use cases.

Others are heavily using data, and looking to scale and mature their data platforms, have robust governance, and perhaps even rearchitect for data availability and efficiency.

While some may be a bit advanced, moving beyond to implement AI in a lot of use cases.

Each stage presents a unique challenge and, in effect, requires a specific kind of leader to help navigate those.

They are looking for leaders who have already made mistakes and learned from them so they can successfully drive outcomes that align with business needs.

You'd be better off finding organizations that are seeking the level of maturity you can help drive.

Putting it together

Now, here's a representative Branding for a Data Leader, combining the niching elements we discussed above:

Data and Analytics leader with 20+ years of experience in Data and Digital Strategy, spanning retail, media, and technology services industries. Drove complex challenges in legacy system modernization, orchestrated a seamless transition to cloud-based infrastructures while mitigating operational disruptions.

Proven track record in implementing modern data architectures, data engineering, advanced analytics, DevOps, and MLOps practices. Skilled in driving data-driven decision-making, promoting data literacy, and leveraging modern cloud platforms to enhance business outcomes.

Notable Career Achievements

• Strategically led extensive Google Cloud migration initiatives for Levis Inc., overseeing the modernization of the entire Data technology stack and achieving a notable 30% reduction in operational costs.
• Implemented a petabyte-scale lake house in the cloud utilizing data fabric architecture principles, replacing outdated Teradata and Informatica platforms, and eliminating over $12 million in licensing costs.
• Streamlined operations by decommissioning legacy Informatica MDM and creating a modern Customer Data Platform (CDP) with robust ID resolution, saving $15+ million in redundant loyalty and rewards accounts.
• Spearheaded the development of cutting-edge AI-based customer segmentation, real-time recommendation, and personalization engines, propelling Levis' revenue growth by over $80 million.
• Engineered a highly efficient Demand forecasting and real-time inventory system at Levis, leading to a remarkable 90% improvement in inventory accuracy and cost savings exceeding $60 million.
• Created and deployed digital twins for customers, marketing, supply chain, and finance teams, resulting in a 30% boost in operational efficiency and fostering innovation across marketing, finance, and supply chain management.
• Developed a Voice of Customer (VoC) platform by integrating reviews and feedback from 70+ sources, extracting valuable insights to optimize customer experiences, satisfaction and driving continuous improvement strategies.
• Pioneered the implementation of a unified campaign management platform at Pandora radio, achieving significant cost savings of $15 million and unlocking over $30 million in conversions and data monetization.

Reading from the above, if I were a hiring manager and were to pick folks who have:

• Retail Industry Experience
• Expertise in building Data Platforms on GCP
• Experience in creating a customer Data
• Have some experience with AI use cases

Viola... I'd be down to just 13 picks as opposed to 190k+ ??

And if I found the above summary in one of the resumes/profiles/outreach messages, I'd be jumping off my seat to get on a call with that candidate.

Because I'd have found my diamond in the ruff.

Hope this helps ????