Responsibilities:
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Work end-to-end across all aspects of data, from engineering and processing to developing advanced visualizations, machine learning models, and experiments.
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Analyze and interpret large-scale (PB-level) transactional, operational, and customer datasets using both proprietary and open-source tools and platforms.
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Transform complex data insights into actionable recommendations and clear visualizations for operational teams and executive stakeholders.
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Operate in a fast-paced environment where rapid execution and time-to-market are critical.
Requirements:
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Bachelor’s or Master’s degree in a quantitative discipline such as Mathematics, Statistics, Actuarial Science, Computer Science, Engineering, or Life Sciences.
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5–8 years of professional experience in Analytics, Data Science, or related roles.
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Self-motivated team player with the ability to quickly learn and apply new tools, techniques, and programming languages.
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Strong analytical curiosity to identify, investigate, and explain trends and patterns in data.
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Excellent communication skills, with the ability to simplify complex concepts for diverse audiences.
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Experience in internal or client-facing consulting/business transformation is a plus.
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Passion for emerging technologies, including Blockchain, AI, and Machine Learning.
Technical Competencies:
Candidates should be proficient in at least two of the following areas:
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Analytical Software: e.g., R, SAS
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Data Visualization Tools: e.g., Tableau, Power BI, QlikView
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Database Management: SQL, NoSQL, Neo4j, or other relational/graph databases
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Programming Languages: e.g., Python, Java, C++, VBA