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Designs, develops and applies programs, methodologies and systems based on advanced analytic models (e.g. advanced statistics, operations research, computer science, process) to transform structured and unstructured data into meaningful and actionable information insights that drive decision making. Uses visualization techniques to translate analytic insights into understandable business stories (eg. descriptive, inferential and predictive insights). Embeds analytics into client’s business processes and applications. Combines business acumen and scientific methods to solve business problems.
Job Responsibility:
Formulates and defines analytics solution objectives and technical requirements based on user needs, an understanding of business processes, industry requirements, and advanced analytic models
Conceptualizes, builds, develops and enhances a client's analytic model
Selects the relevant analytic modeling methodology for the use case, available structured and unstructured data, cost and timing constraints to solve the business issue and deliver clear business focused insights
Embeds analytic models in an enhanced business process of operational system by collaborating with Application Developers
Responsible for measuring business performance based on the model
As a fully functioning analytics team member, applies best practices to analytics solutions and contributes to the development of improved best practices
Leads the model enhancements
Summarizes complex ideas by developing visual models to display insights to simplify user experience
Communicate the analytics solution to the appropriate stakeholders
Requirements:
PhD degree in Statistics, Operations Research, Computer Science or equivalent preferred
Or Master´s Degree in these areas and at least 2-3 years of relevant experience
Advanced knowledge of advanced data science methodologies including but not limited to classical regression, neural nets, CHAID, CART, association rules, sequence analysis, cluster analysis, and text mining
Ability to translate business requirements into mathematical models and data science objectives to achieve measurable business outcomes
Advanced understanding of analytics software (eg. R, SAS, SPSS, Python)
Advanced understanding of analytics deployment architectures
Advanced machine learning, data integration, and mathematical modeling skills and ETL tools (eg. Informatica, Ab Initio, Talend)
Advanced communication and presentation skills
Strong interpersonal skills and effectiveness in working across geographical boundaries
Working knowledge of programming languages such as Python, SQL, R, SAS, Java, Unix Shell scripting
Working knowledge of Hadoop framework desired
Advanced knowledge of data visualization techniques and software tools (eg. Spotfire, SAS, R, Qlikview, Tableau, HTML5, D3)