Data Science & Analytics Jobs

Every day, we all make hundreds of interactions which involve data. This will only increase with the advent of new technology, so data jobs are becoming increasingly important. If you’re looking for your next role as a Data Scientist, Data Engineer or Data Analyst, the specialist recruiters at Salt are here to help.

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Jobs: Data Science & Analytics Jobs

Job Industry: Data Science & Analytics Jobs

Languages: Go, Java (Spring Boot), Scala, .net Core, Python Tools: Kubernetes, Terraform, Docker, Vault, Consul, istio, private cloud, concourse-CI, EFK, Prometheus, Grafana, Firebase Methodologies: Agile, Scrum, Kanban, TDD, BDD, Pair-Programming…

Saudi Arabia

Permanent

Negotiable

What are Data jobs?

The field of data encompasses Data Scientists, Data Engineers and Data Analysts. Data Engineers create the systems which the Scientists and Analysts use to examine data. Data Scientists make predictions based on data patterns. Data Analysts use data to answer questions.

Salary information and career progression

Data AnalystAED18,000 - AED24,000
Junior Data ScientistAED20,000 - AED24,000
Data Scientist (Mid, Senior, Head of)AED25,000 - AED50,000
Data ArchitectAED25,000 - AED32,000
  • Opportunity

    Opportunities for data-related roles are likely to grow as more companies utilise data for their products and services. Emerging fields like the Internet of Things and Blockchain, which allow businesses to work with data in new ways, are also likely to offer Data Scientists, Data Engineers and Data Analysts more opportunities.

  • Recent changes to the sector

    The biggest recent change in the data sector is its increasing focus on AI and advanced Data Analytics. AI is becoming huge, and businesses across most industries are hiring Data Scientists to help them make better business decisions and forecast future performance.

  • Salt’s advice for securing a Data Analyst job

    Employers’ requirements for Data jobs

    Employers looking to fill data roles will prefer candidates who have previously worked with statistics, analytics and applied mathematics. Naturally, experience working in Data Science, Engineering or Analytics is also a big plus, as is having a good knowledge of machine learning capability and associated algorithms.

    • Experience with Hadoop – ecosystem search, Big Data from Apache, data lakes.
    • Experience with Computer Vision, NLP, Deep Learning, Reinforcement Learning etc.

    CV requirements for Data professionals

    Your CV should include relevant work experience, along with technical skills like SQL, Machine Learning, Python capabilities. Industry-specific experience will also help in securing specific roles. For Data Scientists, details of your PhD (if you have one) are desirable including any relevant publications you have in academic journals.

    Interview preparation

    During your interview, you should be prepared to talk about your PhD or any other relevant qualifications you have undertaken. Questions may vary by industry but expect to discuss what you have learned from your previous jobs, and how you would bring that knowledge to the table.

    Educational requirements

    tist applicants will ideally have studied statistics or mathematics academically. Where it is not essential, candidates with PhD qualifications are preferred for high-level Data Science roles or more research-based roles. An MSc in a relevant Data Science field along with a number of years commercial experience will be just as desirable for some clients, it’s important to assess the nature of the company whether it’s research/academic heavy or more real-world problems such as eCommerce or Finance industries.

Top Tip

"A very important tip is to only write on your CV what you are actually able to do. It is easy to list multiple different technologies within Data Science that you have come across but you’ll get found out quickly."

— Caroline Ellis, Principal Consultant

Speak with Caroline Ellis about Data Science & Analytics Jobs

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