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We are hiring a Senior Statistical Analyst to leverage cutting-edge data science tools and methodologies on real-world clinical data for scientific research in precision medicine.
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Candidate will be given the opportunity to learn and make use of sophisticated tools (SQL, Alteryx, Informatica, SAS, Tableau, SSRS, DataRobot etc) and technologies (Big data like Hadoop, Python/R Programming, AI/Data Science,) to provide customized automated solutions across multiple business segments.
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Create new reporting and dashboards, data infrastructure, and queries to track key marketing metrics across multiple data sources leveraging SQL, R/Python, Looker, Tableau, and other visualization tools; monitor for changes in trends, share insights and make recommendations.
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With minimal guidance, write, document, and deploy custom code in a variety of environments (Python, SAS, R, etc.) Perform sophisticated card fraud analyses and strategy support using advanced analytics & data science tools to provide actionable insights and real-time changes to card fraud detection tools that improve business outcomes and minimize fraud risk.
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Advanced proficiency in Qualtrics/Clarabridge, SPSS, SQL, R, Python, Tableau and Power BI. Qualtrics Customer XM and XM Discover Advanced Proficiency, SQL, R, Python, SPSS, PowerBI, Tableau.
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This role will be involved in working with Product Management, R&D, Business, Data Science and Data Architecture teams to design, build, and deploy a leading-edge platform supporting a robust analytics framework for the identification and reporting of illicit activities and associated behavioral patterns of abuse.
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Proficiency in Python, R, or Java and relevant frameworks and libraries. Join us as a Data Science Senior Manager, Generative AI to play your part in that transformation. Excellent project management skills with a proven track record delivering at speed and scale impactful data science solutions on time and within budget.
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Experience with data analytics tools/languages such as SQL, Python, R, Adobe Analytics, Tableau, etc. BA or MA in Statistics, Analytics, Mathematics, Economics, Computer Science, or a related field Familiarity with agile development principles and project management tools such as JIRA and Confluence PREFERREDPrevious work with CDPs, marketing automation, and omni-channel campaign management platforms.
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3+ years experience with Python, Pyspark, R, or other programming languages commonly used in data science. Master's degree in computer science, Data Science, AI, or a related field.
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Comfortable with a high-growth, fast-paced, entrepreneurial environment o Dedication to staying current in rapidly-evolving data science, AI, and ML fields o At least 3 years of experience in a data science or predictive/prescriptive analytics role o Experience with Tableau, Power BI, or similar data visualization tools and techniques o Proficient in Python (or R) and SQL.
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Analyzing large data dets using programming languages such as Python, R, SQL and/or Spark. Employer will accept a Bachelor's degree in Statistics, Operations Research, Applied Mathematics, Economics, Data Science, Business Analytics, Computer Science, Engineering, or a related technical field and four years of experience in job offered or in a Senior Data Scientist related occupation.
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Proficiency in programming languages such as Python, R, or Java. Responsibilities: The Director of Data Science and Insights will be responsible for the overarching vision, strategy, and implementation of Novelis' advanced analytics and AI capabilities, focusing on enhancing operations in sales, marketing, and other key business areas globally.
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Utilizing Data analytics skills and experience developing mathematical models in R, Python, SAS, MATLAB, and/or SPSS; Construction Management, Materials Science, Materials Science and Engineering, Project Engineering & Management, Risk Management, Civil Engineering, Mechanical Engineering, Electrical Engineering, Industrial Engineering.
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Experience using SAS, R, Python, or other programming languages (e.g., classical statistical modeling, machine learning, bioinformatics computational modeling, etc.) The qualified candidate should be currently pursuing or have received a doctoral degree in the one of the relevant fields (e.g. statistics, mathematics, bioinformatics, computer science, data science, epidemiology, or data-related field.
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Extract, clean, and analyze large datasets using Python, R, and/or SQL. Bachelor’s degree in Data Science, Statistics, Economics, Computer Science, Business Administration, Finance, or a related field.
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