Value Driven Data Science: Boost your impact. Earn what you’re worth. Rewrite your career algorithm.

One of the biggest risks for independent data professionals is spending months or years developing a product or service that nobody wants to buy. The graveyard of failed data science projects is fill…

The traditional career path of climbing the corporate ladder no longer appeals to many data scientists - who crave freedom and ownership of their work. Yet the leap from employment to independence ca…

The right book at the right time can completely transform your career trajectory, but many data professionals struggle to find resources that directly address their unique challenges of bridging tech…

Many data scientists begin their careers expecting to influence strategic decisions, only to find themselves trapped as "data order takers" - endlessly running reports and responding to requests with…

Even the most compelling data presentation can fail if it runs headfirst into your stakeholders' cognitive blind spots. Decision makers who claim to be "data-driven" often unconsciously filter inform…

Data storytelling might make your findings memorable, but persuasion is what gets your recommendations implemented. 

Many data scientists have mastered communication and storytelling, yet still watch …

Social media data drives countless business decisions, but up to 40% of social media engagement may be artificial or manipulated by bots. For data scientists accustomed to cleaning messy data, delibe…

Social media algorithms silently shape what billions of people see and how they interact online. While most data scientists work to optimize business value within platform rules, there's valuable kno…

Most dashboards and reports get ignored despite all the technical expertise that goes into creating them. The reason isn't technical limitations or poor data quality - it's that they fail to deliver …

Despite unprecedented data abundance and widespread data science education, even experienced data professionals still struggle to interpret data effectively. They draw wrong conclusions, miss critica…

Can you clearly articulate what makes your data science work valuable - both to yourself and to your key stakeholders? Without this clarity, you'll struggle to stay focused and convince others of you…

Internal data science teams face a unique challenge - they're providing an invisible service that only gets noticed when something goes wrong. This puts data scientists in the awkward position of hav…

When deadlines loom, it's easy for data scientists to fall into the trap of cutting corners and bending analyses to deliver what stakeholders want. But what if a simple framework could help you maint…

The data science world has always been obsessed with tools and techniques - a fixation that's only intensified in the era of generative AI. Yet even as ChatGPT and similar technologies transform the …

Even the most brilliant data analysis can fall flat when presented with poor visualisations. Many data scientists simply use default charts from their analysis software, missing the opportunity to cr…

Data scientists can often find themselves in a frustrating cycle - meticulously executing stakeholder requests only to discover what they delivered isn't what was actually needed. The disconnect betw…

Looking for powerful AI tools that can dramatically boost your impact, regardless of the size of the businesses you serve? 

You don't need an enterprise-size budget to transform your work and create m…

While most data scientists chase after scraps at the big business table, a hidden gold mine sits completely ignored. Small businesses are desperate for AI solutions but can't get help because everyon…

Would you believe that sharing a conversation in the lunch room could be more valuable to your data science career than spending countless hours behind a computer, perfecting algorithms and models? I…

If you want to succeed in data science, you need to create business value. But what does business value actually mean to the executives with the power to make or break your data science initiative?

In…