High ROI Data Science

High ROI Data Science, authored by Vin Vashishta, targets founders and top tech companies, delivering insights on AI strategy, product development, and technical deep dives. It addresses the implementation challenges and opportunities of AI, fostering a data-centric culture in businesses, career advancement in data science, and the transformative potential of generative AI.

AI Strategy and Implementation Data Science Career Growth Generative AI Applications AI and Automation in Business Data-Driven Decision Making Organizational Adaptation to AI AI in Retail and Customer Service Marketing Analytics Leadership and Management Trends AI Disruption and Competitiveness

The hottest Substack posts of High ROI Data Science

And their main takeaways

Who’s Hiring And Paying The Best For Data Roles?

255 implied HN points • 04 Feb 24
💼 Business Jobs Salaries
  1. In times of economic uncertainty, it's crucial to work for companies that offer top compensation, interesting projects, and stability to excel in your career.
  2. Data analysts and mid-level data leaders are facing challenges with salary declines and shifting demands, necessitating reskilling into safer roles like data engineering or AI product management.
  3. Data engineers are still sought after, but the market is becoming more competitive, requiring advanced skills like handling streaming data. AI product managers are in high demand, with lucrative compensation up to $300K.

It's A New Year, But Businesses Are Still Baffled By The Same Old Problems With Data And AI

314 implied HN points • 15 Jan 24
🕹 Technology AI Data Business Digital Transformation
  1. CEOs face challenges with limited skills and expertise in implementing AI initiatives.
  2. Businesses struggle with data complexity and ethical concerns when it comes to utilizing AI.
  3. Companies need to align AI opportunities with business goals, estimate costs upfront, and prioritize continuous reskilling for successful AI implementation.

What Are Companies Doing With Generative AI? A Tale Of 3 Strategies.

294 implied HN points • 12 Jan 24
🕹 Technology AI Retail Data Strategy E-commerce
  1. Companies are using Generative AI tools to decrease training times and improve customer service in retail.
  2. Some companies are implementing Generative AI without a clear business problem statement, leading to undefined outcomes.
  3. Retailers like Walmart are strategically using Generative AI to change customer workflows, improve online shopping experiences, and increase revenue.
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Long-Chain Marketing: How Data Engineering & Data Management Create Value For The Business

294 implied HN points • 10 Jan 24
💼 Business Data Engineering Data Management Value Creation Marketing
  1. Understanding the long-chain in marketing is crucial for connecting business outcomes with data and metrics.
  2. Data engineering and knowledge management are essential for transforming data into valuable assets that can be monetized by the business.
  3. Long-chain marketing involves seeing marketing efforts as part of a longer sequence of actions that lead to business outcomes, rather than standalone events.

What Does It Take To Create Longevity And Stay Relevant In The New Work World?

176 implied HN points • 23 Jan 24
💼 Business Career development Market Trends Skill development Productivity
  1. Success in the new work world requires being forward-looking and prescriptive, not just reacting to trends.
  2. Manufacturing luck involves positioning early in emerging trends to have more opportunities and be better prepared.
  3. To stay relevant, focus on upskilling in areas that align with future trends and combine vision, follow-through, and productivity.

What To Do When You're Stuck At A Business That Doesn't Care About Data Science

353 implied HN points • 27 Feb 23
💼 Business Data science Leadership Strategic Planning
  1. Many data scientists in companies that don't prioritize data science end up doing basic reporting and analytics.
  2. Technical management in such companies often lack the understanding and incentives to support data initiatives.
  3. Navigating a lack of data culture and strategy in a company requires significant effort but can lead to valuable career opportunities.