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NumPy Developer Salary in the US and UK compare to Ukraine

NumPy Developer Salary in the US

The average NumPy programmer salary in the US is $115,000 a year and hourly rate is $70. Entry level positions start at $50,000 a year while most experienced consultants make up to $145,000 a year. These numbers are based on the salaries parsed from Indeed.com job descriptions in June 2018. The most of the developers are needed today in:
Austin, TX, New York, NY, San Francisco, CA

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Latest NumPy Jobs in the US

1 Data Science Intern - Summer 2018 - new SciPy, NumPy, Pandas, NLTK, Matplotlib. Join Myers Media Group and work with a fun, fast-paced team that is changing the Macro SEO(Search Engine Optimization)...

2 Python Engineer - new Vast understanding of Pip, Flask, NumPy, Anaconda, PyCharm, or similar tool stack and ability to coach junior developers on their usage....

3 Python Architect - new Vast understanding of Pip, Flask, NumPy, Anaconda, PyCharm, or similar tool stack and ability to coach junior developers on their usage....

4 Senior Scientist, Data Science Architect - new Strong working knowledge of data science enabling modules such as (keras, tensorflow, scikit-learn, numpy, scipy), architectures, and design patterns....

5 Software Engineer - new Experience using scientific Python libraries and tools like Pandas, Anaconda, and NumPy. WHO OUR CLIENT IS:....

NumPy Developer Salary in the UK

The average NumPy expert salary in England is £55,000 a year and hourly rate is £34. Begginer level positions start at £35,000 a year while most experienced developers make up to £80,000 a year. These numbers are based on the salaries parsed from Indeed.co.uk job descriptions in June 2018. The most of the developers are required at the moment in:
London

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Latest NumPy Jobs in the UK

1 Python Developer - new Python Developer 3 month contract Didcot A Python Developer is needed for a 3 month contract based in Didcot. This position will be working for an...

2 Data Architect (UK 1011) Knowledge in machine learning and deep learning frameworks like Spark-ML, Python scikit-learn, pandas, numpy, sparklir, tensorflow and H2O....

3 Python Developer Numpy, Pandas, Dask or SciPy. Austin Fraser Technology are working with a leading software house in Berkshire to seek an experienced Python Developer to join...

4 Natural Language Processing Engineer You are familiar with Python NLP/ML libraries like NLTK, scikit-learn, numpy, scipy, etc. 16th July 2018....

5 Data Scientist (Water Management) Experienced in data science and analytics for decision-making, for example using popular data science libraries such as Pandas, Numpy, Matplotlib, ggplot, etc....

How much do developers make in other technologies? Take a look at SQL, Sitecore, Salesforce, Sails.js, Scala, AWS, Force.com, SCADA, Redis, PhantomJS, NumPy, JavaScript, Umbraco, Heroku, CouchDB, Redux, VoIP

The True Cost of Hiring an In-house vs Remote NumPy Developer in Ukraine

Sometimes hiring managers face the “in-house vs outsource”. The biggest mistake CTOs, CEOs, and startup founders make when choosing (and comparing) developers is: they ignore the embedded costs. Actually, there are numerous and substantial costs involved in hiring and maintaining employees. An in-house developer (or any employee) is always more expensive than his salary when you factor in embedded costs which aren’t reflected in the employee’s salary:
  • employee benefits (+10%)
  • administration and infrastructure (+10%)
  • paid leaves (+10%)
  • training (+5%)
  • management (+5%)
  • recruitment (+10%)

The outsourcing provider copes with the same embedded costs (though maybe in less amounts). The only difference is it had already factored these costs into its price quote. So, let’s take a fresh look at the adjusted (salary + 50%) numbers.

PeriodUS vs UkraineUK vs Ukraine
1 dev/m$13,750$3,200£6,250£2,400
1 dev/y$165,000$38,400£75,000£28,800
10 devs/m$137,500$32,000£62,500£24,000
10 devs/y$1,650,000$384,000£750,000£288,000
US = United States, UK = United Kingdom
In this scheme, outsourcing to Ukraine is the most cost-effective choice.

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