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Big Data Principle Professional - Mobily Jobs in Saudi Arabia

 

Is Big Data a good career?
Depending on the specific position along with your skill and education level, big data jobs are very lucrative. Most pay in the range between $50,000 – $165,000 a year. Not only is big data a rewarding career that exposes you to the latest in technology, but it also provides a nice living for you
What is the scope for big data?
More and more companies are recognizing the importance of Big Data as a source to gain insights and make informed decisions. And Data Analytic specialists who can define Big Data, uncover hidden patterns, spot opportunities, and create insights for the betterment of a business are in high demand. 
What skills do you need for big data?
Top Big Data Skills
  • Analytical Skills. ...
  • Data Visualization Skills. ...
  • Familiarity with Business Domain and Big Data Tools. ...
  • Skills of Programming. ...
  • Problem Solving Skills. ...
  • SQL – Structured Query Language. ...
  • Skills of Data Mining. ...
  • Familiarity with Technologies.

Big Data Jobs in Mobily KSA

  • Company: Mobily
  • Employment Type: Full Time
  • Education Level: Master
  • Experience: 7 Years
  • Job Type: Marketing

Job Summary

  • Design, build and implement outstanding, robust, actionable analytical business solutions makes use of big data including structured data (ex: Teradata based customer database, large analytical table, offers response) and unstructured data (social media interactions, network transaction, survey response, web browsing, customer foot-falls) to identify the best practice for big-data use cases in line with business objectives.
  • Communicating complex analytical and technical concepts to a business audience.
  • Identify key questions that can be answered with data and advanced analytics, leveraging unstructured, noisy and big data where appropriate.
  • Formulate the analytical approach and data acquisition strategy to answer the questions identified
  • Go through all phases and iterations required to deliver analytical solutions, from data exploration, cleansing or feature creation to building models and creating compelling visualizations, making sure the solution answers a relevant business problem
  • Conduct data discovery and exploration for unstructured data and perform the standard preprocessing procedures.
  • Visualize and tell stories with data, take decision based on this data and present results to business areas
  • Develop and deliver model’s outcome and performance reporting, critical for tracking and managing the business, including weekly, monthly, and quarterly operational metric reports.
  • Identify new datasets to be capturedto enrich the drive analytical attributes.
  • Design, develop and maintain algorithms to extract relevant information from big amounts of data, scalable software systems and algorithms to clean, standardize, and analyze raw data.
  • Evaluating and differentiating techniques, tools and approaches to Deep Learning problems
  • Explanation and documentation of analytical model’s techniques and results.
  • Development of SQL to enhance existing stored procedures.
  • Maintain already developed automated end-to-end flow.
  • Write clean, scalable and fast performing code according to guidelines and quality standards (solid principles, code readability, pattern use) and review other developers’ code.
  • Drive the implementation of the analytical strategy and work with functional business leaders to build scalable processes and metrics.
  • Pursue the generation of common components and best practices of big-data use cases and fostering the reuse of big-data technology and platform.
  • Participate in “make” vs. “buy” decisions from a technical point of view concerning technology.
  • Demonstrated track record of prototyping and launching industry leading big-data solutions.
  • Spearhead innovation in the application of data analytics to highlight the potential use cases for external big-data monetization.
  • Participating in learning and training initiatives for the wider analytics teams

Skills

  • Strong Background in Predictive modelling , Machine Learning, Data mining and Artificial Intelligence, including: Support vector machines, Bootstrap aggregating / bagging, Cluster analysis, Cascading classifiers, Decision trees, Time series analysis & time series forecasting, Boosting, Factor analysis, Structural equation modelling, Item response theory, Markov chains, Voronoi diagrams, Neural networks, Genetic algorithms, Data visualization, Bayesian modelling, Multivariate regression, Logistic regression, etc.
  • Solid understanding of data management, implementation of machine learning algorithms and various statistical modelling techniques.
  • Good understanding of the science behind machine learning algorithms (supervised and unsupervised algorithms), statistical and optimization techniques.
  • Ability to attach complex business questions with data and curiosity to dive deep, identifying the root cause and “so what” rather than just the trends.
  • Thrive in an environment that is tasked with providing data-driven decision support and business intelligence that is timely, accurate and actionable.
  • Eeffective prioritize projects, manage multiple competing priorities simultaneously and drive projects to completion under tight deadlines.
  • Experience in data mining using databases in a business environment with large-scale, complex datasets.
  • Effectively communicate with both business and technical teams.
  • Think big, understand business strategy, provide consultative business analysis, and leverage technical skills to create insightful, effective BI solutions.
  • Hands on experience in SQL, PL/SQL, Excel, Linux and OLAP, SAS, Scala, R, Python (data extraction, manipulation, data insights).
  • Experience with data presentation and visualization tools (Shiny, Tableau, Power BI, JasperSoft, QlikView, MicroStrategy, Business Objects) and able to translate complex insights in a story telling dashboard.
  • Good understanding of Hadoop Ecosystem components, Hadoop MapReduce framework, streaming processing frameworks.
  • Experience of Hadoop-based analytical tools (Mahout, Hive, Pig. RHadoop, MOA, Jabatus, Alpine, etc.)
  • Proficiency in query languages like Hive and NoSQL databases like HBase.
  • Graph analysis, Geo-spatial analysis and NLP is plus.
  • (PhD is a plus).

Education

Quantitative discipline – Computer Science Engineering/ Applied Mathematics/ Statistics, or related

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