Key warning signs for data scientists and tech professionals to consider before joining a new data team, covering data infrastructure, team roadmap, and role clarity.
A podcast interview discussing common ML mistakes, quantifying impact, and career growth for machine learning engineers.
An interview with data scientist Eugene Yan discussing his career path from psychology to Amazon, favorite ML projects, and advice for aspiring data scientists.
A guide for data science leaders on how to strategically select the most impactful problems for a team to work on, using frameworks like cost-benefit analysis.
A data scientist shares key strategies for winning a data hackathon, based on judging Hacklytics 2021, covering evaluation criteria and time-saving tips.
A data science leader shares insights on hiring, training, and managing effective data science teams, based on experience at Lazada and uCare.
Advice for experienced data scientists on optimizing their resumes to attract recruiter attention, covering side projects, Kaggle, and academic work.
Advice on avoiding or handling data science job mismatches by scrutinizing job descriptions, asking key interview questions, and researching team culture.
Explores the intrinsic motivations for building a data science portfolio beyond just getting a job, covering learning, helping others, and enjoyment.
A podcast interview with data scientist Eugene Yan discussing his career transition, data science leadership, and experiences at Lazada.
A senior data scientist offers advice on handling imposter syndrome and meeting higher expectations after a promotion to a senior role.
Argues that data scientists should own the entire process from problem identification to solution deployment for greater impact and efficiency.
A data scientist shares practical habits and workflows for executing successful data science projects, focusing on research, experimentation, and team alignment.
Answers common questions about data science in business, covering requirements, model interpretability, web scraping, and team roles.
A data scientist shares three essential pre-project tasks—the one-pager, time-box, and breakdown—to avoid common pitfalls and ensure project success.
A data scientist shares how adopting Scrum, despite initial resistance, improved project management and delivery for data science teams.
A data scientist analyzes why a simple 'wish list notification' feature won a major hackathon over more complex, high-tech ideas.
A guide on preparing and delivering effective data science presentations, covering motivation, topic selection, and storytelling techniques.
A data scientist clarifies common misconceptions about the field, explaining that machine learning is only a small part of the job and advanced degrees aren't always required.
Explores adapting Agile/Scrum frameworks for data science teams, covering effective practices and necessary adjustments for the unique challenges of data science work.
