Hiring Dask developers? Then you should know!
How and where is Dask used?
- Machine Learning: Predictive Analytics
- Data Analysis: Large-Scale Processing
- Parallel Computing: Distributed Computing
- Big Data: ETL Pipelines
- Scientific Computing: Simulation Models
- Finance: Risk Management
- Genomics: DNA Sequencing
- Weather Forecasting: Meteorological Simulations
- Image Processing: Computer Vision
- IoT: Real-time Data Streaming
Compare Junior, Middle, Senior, and Expert/Team Lead Dask Developer roles
Seniority Name | Years of experience | Responsibilities and activities | Average salary (USD/year) |
---|---|---|---|
Junior | 0-2 years |
| $60,000 |
Middle | 2-4 years |
| $80,000 |
Senior | 4-6 years |
| $100,000 |
Expert/Team Lead | 6+ years |
| $120,000 |
Quick Facts about Dask.
- Dask, the parallel computing framework, sprouted in 2014.
- Data science, machine learning, and parallel computing adore Dask.
- To delve into Dask, a basic understanding of Python is required.
- Apache Spark is a close contender to Dask in popularity.
- Did you know Dask can handle petabyte-scale data effortlessly?
TOP Dask Related Technologies
- NumPy
- Pandas
- Matplotlib
- Scikit-learn
What are top Dask instruments and tools?
- Dask Distributed: Tool for parallel computing – released by Dask Development Team
- Dask ML: Machine learning library – released by Dask Development Team
- Dask DataFrame: Parallel computing with DataFrame – released by Dask Development Team
- Dask Array: Parallel computing with NumPy arrays – released by Dask Development Team
- Dask Delayed: Parallel computing with custom task scheduling – released by Dask Development Team
Talk to Our Talent Expert
Our journey starts with a 30-min discovery call to explore your project challenges, technical needs and team diversity.
Maria Lapko
Global Partnership Manager