Lead, manage, and coach the team to deliver outcomes efficiently and in a timely manner.
Strategically design and apply advanced analytics in business using design thinking methodologies, AI/ML insights, and advanced modeling, establishing execution roadmaps and alignment with key stakeholders.
Generate new analytical ideas and initiatives to enable business opportunities.
Ensure the successful delivery of advanced model initiatives/designs to development, meeting agreed quality and business targets.
Attract and lead a team to generate useful insights from advanced analytics and modeling to drive and improve execution performance.
Perform large-scale data analysis and develop effective machine learning or statistical models, segmentation, classification, pattern recognition, optimization, etc., on large and complex data sets.
Develop, build, and test statistical and computational models that serve as key inputs for real-time contextual marketing tools.
Identify business opportunities, actionable insights, and suggest recommendations for data-driven marketing campaigns.
Collaborate and establish trust-based relationships with stakeholders to provide impactful analysis and insights that align with business objectives.
Work closely with other BI functions and campaign operations to provide end-to-end analytical solutions and proactively create and test decision rules for marketing campaigns.
Qualifications:
M.S./Ph.D. in a quantitative field such as Mathematics, Statistics, Data Science, Computer Engineering, or a related field.
At least 5 years of professional experience in analytical or modeling areas or related fields in a mid-senior management role.
Excellent analytical skills, with an understanding of the fundamentals of statistics and experimental design.
Deep understanding of statistical modeling, predictive modeling, propensity models, and machine-learning algorithms and deep learning techniques.
Full stack experience in data understanding, collection, aggregation, analysis, visualization, productionization, and monitoring of ML products.
Experience in data engineering, working with big data technology (Spark), and cloud platforms such as AWS, Azure, or GCP is a plus.
Ability to manipulate and analyze complex, high-volume, high-dimensionality data from varying sources.
Ability to communicate complex analysis in a clear, simple, and actionable manner.
Working knowledge of SQL and relational databases, as well as analysis tools such as R, SAS, Python, or Matlab.
Experience in the Telecom industry is an advantage.
Experience analyzing data from 3rd party providers such as Google Analytics, Facebook Insights, Adwords, etc., is an advantage.
Good command of English.
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