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Do you agree? - DSBoost #36
Communication is the most sought-after skill in DS.
Jobs-in-data.com studied 9,261 job descriptions from their site to explore the difference between ‘Machine Learning Engineer’ and ‘Data Scientist’ job posts.
Here are some takeaways:
ML Engineers > ML Ops > Data Scientist. That is the ranking in salaries for all seniority levels.
Machine Learning salary is 15-40% higher than Data Science salary.
On the regular level ML Engineers have a 38% higher median salary compared to Data Scientists.
ML positions have a higher demand for Ph.D. holders. (27% vs 23%)
In some ML positions you will find C and Java while in DS positions SQL. However, Python is still king:
DS positions focus on statistics and data visualization, while ML jobs are more towards deep learning skills, especially in tools like PyTorch and TensorFlow.
Communication is a requirement in 3/4 of the positions. This fact also shows that these positions are usually cross-functional and interaction with others is part of the everyday tasks.
The goal of data roles is to get insights and make better decisions.
Effective communication ensures that insights and findings are clearly understood by coworkers or stakeholders.
Educating others about the data process and eli5 methodologies can also be a task. With efficient communication, you can make others feel that they understand the data as well.
If you are a good Data Scientist or ML engineer but bad in communication you will be lost in this field.
This thread may help you to be better at it:
If you are into MLOps focus on data processing technologies like Spark, Databricks, and Snowflake!
Regarding cloud AWS dominates. But it is more important for ML jobs than DS positions.
Regarding visualization tools Tableau and Power BI are the leading technologies. Nothing surprising here.
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Interestingly Excel is still huge in DS positions. It is a requirement in 10% of the job postings.
That is probably more relevant in a cross-functional role where most of the employees are still working with Excel spreadsheets.
Bad news for juniors
“Out of 4,325 Data Scientist job listings, a mere 4% are targeted towards Junior or Intern positions. Similarly, Machine Learning Engineer positions, which totaled 2,732, showed that only 3% were available for those at the junior or intern level. Even more striking is the scenario in ML Ops – with a sample of 1,367 jobs, only a scant 1% were reserved for newcomers.”
Again, this was an extract from this interesting post by jobs-in-data.com
Make sure to check out the original article! It is an awesome read!