Job Description

Mission/ Core purpose of the Job: • To deliver keen and smart solutions via moving dynamics of the system, • To efficiently solving complicated business problems, •To deliver automated and systematic data engines which facilitates and increases transparency of the process, • To collect and process required data for Data Processing and Storage Systems (i.e. DPSS) from multiple internal and external sources, • To liaise with ITS to supply and maintain required infrastructures including hardware, software, information flow and data engines. Task Complexity: • To build high-performance algorithms, prototypes, predictive models and proof of concepts • To refine and tune data models to be able to respond to various homogeneous data structures • To deploy proper experiments on data in order to ensure about the applied data to be thoroughly clean, reliable and not corrupted • To measure effectiveness of the designed data collection methods in order to find the most effective way • To exploit multiple new/existing algorithms for processing raw data to generate real business value • To analyze and also validate interpretation of data which has been led into information insight • To prepare reports of predictions and findings for management through effective data visualizations and reports • To propose and design Data-efficient models that are smartly developed in accordance with the quality of existing data. • To process huge volumes of data collected from multiple internal and external sources • To employ sophisticated analytics programs, machine learning and statistical methods to do both predictive and prescriptive modeling • To search and propose various ways in order to compensate for unavailable required data by doing scientific experiments • To liaise with various Marketing teams in order to collect data and induct them of Data Science concepts in order to address business requirements • To collect and process huge volumes of data from multiple internal and external sources, • To develop and support data/information analysis and visualization dashboards also prepare insightful report for related internal teams and management, • To validate the interpretation of data before that being used in the data engine, • To propose and contribute in selection of the most efficient software and platform to develop data engines per case, • To be responsible for fixing interruptions that may occur in the information flow, • To identify data engine requirement in order to maintain efficiency of systems in terms of required resources (i.e. hardware and effort), • To search and look for efficient ways in order to compensate for unavailable required data by doing scientific experiments, • Designing data-efficient models that are smartly developed in accordance with the quality of existing data, • To refine and well tune databases at the time of facing sudden changes in requirements, • To clean and tune stored data to be thoroughly clean, reliable and not corrupted, • To support manager in actively detecting and cleaning redundant data from DPSS middle ware, • To propose proper data structure for the data analytics end, • To develop the mapping, extraction, and unification (ETL) pipeline of data from numerous structured and unstructured data sources for visualization and mining in novel applications, • To implement complex queries utilizing Database programming Commands, Views, Stored Procedures, • To actively document methods and procedures applied in the aim of data analytics, • To liaise with various departments and outsourcing partners in order to reflect Data Science engineering platforms and system requirements, also initiate required changes in this regard, • To build high-performance algorithms, prototypes, predictive models and proof of concepts, • To refine and tune data models to be able to respond to various homogeneous data structures, • To deploy proper experiments on data in order to ensure about the applied data to be thoroughly clean, reliable and not corrupted, • To measure effectiveness of the designed data collection methods in order to find the most effective way, • To exploit multiple new/existing algorithms for processing raw data to generate real business value, • To analyze and also validate interpretation of data which has been led into information insight, • To prepare reports of predictions and findings for management through effective data visualizations and reports, • To propose and design Data-efficient models that are smartly developed in accordance with the quality of existing data, • To process huge volumes of data collected from multiple internal and external sources, • To employ sophisticated analytics programs, machine learning and statistical methods to do both predictive and prescriptive modeling, • To search and propose various ways in order to compensate for unavailable required data by doing scientific experiments.

Requirements

Education: • BS in Engineering, Operations Research, Soft Computing, Computer Science, Analytics, Mathematics, Computational Finance or Statistics. Experience: • Minimum of 3 years’ experience in an area of specialization (preferred to be data science/data analysis) Knowledge: • Working knowledge of database administration and data warehouse, • Soft computing, • Parallel processing, • Graph theory and applications, • Programming, • Artificial intelligence, • Forecasting techniques, • Having a good working knowledge of internal and external data sources, • In-time estimation of the required hardware to deploy a DPSS. Skills: • Database Programming languages Advanced, • ETL and OLAP, • Algorithmic thinking and coding, • Parallel processing skills, • Creative problem solving skills, • Intellectual curiosity, • Negotiation skills, • Good communication skills, • Interpersonal skills, • Analytical skills, • Project management skills, • Being quite skilled in applying massive parallel processing techniques, • Leverage tools various data processing programming languages to drive efficient analytics.

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