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Data Analyst / Data Scientist
Location
Saudi Arabia
Posted
79 days ago
Salary
0
Seniority
Senior
Job Description
Data Analyst / Data Scientist
nybl
• work closely with nybl to identify issues and use data to propose solutions for effective decision making • build algorithms and design experiments to merge, manage, interrogate and extract data to supply tailored reports to colleagues, customers or the wider organisation • use machine learning tools and statistical techniques to produce solutions to problems • test data mining models to select the most appropriate ones for use on a project • maintain clear and coherent communication, both verbal and written, to understand data needs and report results • create clear reports that tell compelling stories about how customers or clients work with the business • assess the effectiveness of data sources and data-gathering techniques and improve data collection methods • horizon scan to stay up to date with the latest technology, techniques and methods • conduct research from which you'll develop prototypes and proof of concepts • stay curious and enthusiastic about using algorithms to solve problems and enthuse others to see the benefit of your work.
Job Requirements
- Experience and knowledge in statistical and data mining techniques using (e.g., python, R, SQL)
- Experience and knowledge in applying advance Machine Learning techniques (e.g., Neural networks, supervised and unsupervised ML, computer vision and image processing, text analysis)
- Experience and knowledge in big data analysis and management and distributed computing tools (e.g., Hadoop, Hive, Spark)
- Experience and knowledge in one or more programming languages (C, C#, Java)
- Experience and knowledge in web development frameworks (javascript, React, node.js)
- Experience analyzing data from 3rd party providers: (e.g., Google Analytics, Site Catalyst, Facebook Insights)
- Experience visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot, etc.
- Experience working with and creating data architectures
- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks
- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications
- Excellent written and verbal communication skills for coordinating across teams
- A drive to learn and master new technologies and techniques
- Willingness to learn new technology
- Able to work independently on researching solutions and applying findings.
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