Our client

Our client is providing an advanced transport network for the people of Dubai. They have been high on the government’s agenda, which is evident from its initiatives to enhance the public transport facilities and improve roads across the emirate to make travel safer and smoother. Our client is responsible for planning and providing the requirements of transport, roads & traffic in the United Arab Emirates.

Job Purpose

Creating and maintaining data architectures focused on client goals and customer needs that capitalizes on business intelligence and big data technologies to improve the value of data, improve effectiveness of information stewardship, and streamline the flow of data.

Key Results Accountabilities

• Projects: Support or Manage data management programs and projects including complex business intelligence and big data programs and projects as required.
• Guide oversight of the development of client Implementation Plan for Dubai Data.
• Advise client data professionals on how to ensure that the benefits of open and shared data are maximized, through high levels of adoption and utilization of the data to improve services and decision-making.
• Advise on identifying the right skills and establish the necessary roles within client Department, as outlined in the Dubai Data Manual
• Key support in identifying and enabling the delivery of data sets to the Dubai Data Platform for both Open and Shared Data publication, and appropriately applying the Data Classification Framework to their Data.
• Designs and develop Big Data models to consolidate and analyze unstructured, diverse “big data” sources which can be used to generate fact and prediction based solutions Business Units.
• Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers.
• Develop market "mash up" by combining internal corporate data and applications with externally sourced data.
• Identify and recommend analytics tools to enhance data quality and integrity.
• Identify actionable insights through data science and measurable values to translate into concrete initiatives.
• Designs, develops and programs methods, processes, and systems to consolidate and analyse unstructured, diverse “big data” sources to generate actionable insights and solutions.
• Develops and codes software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources.
• Strategy: Conducts in-depth analysis of business intelligence and big data architecture elements and identify target architectures and gaps from baseline in line with client technology strategy.
• Enterprise Architecture: Supports in developing and implementing data governance practices and standards to enhance and maintain an accurate, complete, secure and reliable data architecture.
• Enterprise Architecture: Creates, reviews, and improves client data architecture practices and standards including but not limited to BI and big data, metadata management, data catalogues, data classification, and data quality management.
• Innovate in Big Data to create capabilities such as smarter usage of past performance data that can be used for predicting and driving future operational efficiency, market prediction etc.: serve as an asset providing Group operating leverage.
• Identify questions and issues for data analysis and experiments and develops and codes relevant programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources.
• Develop and maintain the models on the enterprise Data Lake, Group Big Data cloud, and associated platforms, tools, process and practices for Data driven insights.
• Support the development and delivery of rapid software prototypes preferably using Python, using machine learning models and data analysis, Artificial Intelligence, distributed algorithms, tools such as Mat Lab and R etc. to demonstrate value of technology and ideas.
• Design and develop methods to consolidate, analyze and handle large scale data (structured and unstructured) and/or big data platforms which offers appropriate exposures and tools to executives for decision making, tools for operating teams to make smarter decisions everyday.
• Apply bigdata and data mining techniques, statistical analysis and build high quality prediction systems integrated with the groups Systems.
• Perform other responsibilities associated with the position as appropriate.

Knowledge, Skills and Experience

• Master’s in data science/ Computer Science/Statistics/ Mathematics/ Research from a recognized university.
• Goal-driven leader who maintains a productive climate and confidently motivates, mobilizes, and coaches employees to meet high performance standards.
• Proficiency with NoSQL databases, such as MongoDB, Cassandra, HBase
• Results-driven achiever with exemplary planning and organizational skills, along with a high degree of detail orientation.
• Deep understanding of and experience with machine learning models and data analysis, Artificial Intelligence, development of distributed algorithms, Tools such as Mat Lab and R etc.
• Experience with data visualization tools.
• Innovative problem-solver who can generate workable solutions and resolve complaints.
• Proficiency in using query languages such as SQL, Hive, Pig.
• Have experience with various best practices/standards in the market such as DAMA, MIKE 2.0, TOGAF, and COBIT.
• TOGAF and Cobit certification.
• Hands-on experience with Hadoop and Big Data management technologies (Apache Hadoop, Cloudera, etc.) preferred.
• Resourceful team player who excels at building trusting relationships with customers and colleagues.
• Flexible team player who thrives in environments requiring ability to effectively prioritize and juggle multiple concurrent projects.
• Experience handling large scale data and/or big data platform and tools.
• Exceptional listener and communicator who effectively conveys information verbally and in writing.
• Experience with common data science toolkits, such as R, Python, Mat Lab, Weka, NumPy, etc.
• 10 years of working experience.
• Excellent understanding of machine learning techniques and algorithms, such as kNN, Naive Bayes, SVM, Decision Forests, etc.
• Highly analytical thinking with demonstrated talent for identifying, scrutinizing, improving, and streamlining complex work processes.
• Computer-literate performer with extensive software proficiency covering wide variety of applications.