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Ability work with stakeholders to drive project ideas and turn them into rigorous solutions Expert knowledge of Python and SQL Desired Characteristics Working experience with product teams to deploy prescriptive machine learning models to drive one or more KPIs. Knowledge of enterprise-level digital analytics platforms (e.g. Adobe Analytics, Google Analytics, etc.
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Own machine learning development lifecycle activities and execute on crucial timelines and milestones. Familiarity with machine learning engineering and developing/implementing machine learning models within AWS or other cloud platforms.
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DATA STRUCTURES AND ALGORITHMS In our Data science track we prepare you to get job as one of the following: Python developer, a data analyst, data visualization developer, a statistician, a machine learning engineer or a data scientist.
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Excellent communication skills to collaborate with stakeholders in engineering, data science, machine learning, and product. As a staff engineer, you will partner with your team and partner teams like machine learning, and Ads to create and improve scalable, fault tolerant, self-serve systems.
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This candidate should be proficient in using BI tools such as Tableau, in addition to experience with one or more modern technologies such as relational databases, AWS, Snowflake, Python, Databricks, Git, and Machine Learning.
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The opportunity: The Senior Data Scientist I role will provide advanced analytics support within the Business Analytics function that applies the power of data with machine learning to improve business outcomes across the Health and Risk Solutions business.
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C, Java, Python, R, or Matlab, software applications in Linux, UNIX, Windows environments, data analysis algorithms, data management approaches, relational databases, or machine learning algorithms.
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Experience using computer languages (Python, SQL) to manipulate data and draw insights from large data sets, including cloud-based Snowflake, AWS SageMaker, Azure AI Services and MS Power AppsKnowledge of machine learning techniques (clustering, decision trees, neural networks, graph ML, OCR, sentiment analysis, etc.
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Demonstrates proficiency in time series ensemble modeling, multivariate regression and classification, survival analysis, cluster analysis, design of experiments, and machine learning algorithms learning algorithms.
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Qualifications: Extensive experience in data engineering, data analysis, and machine learning. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data.
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Highly proficient in at least one popular programming language used for Machine Learning, such as Python or R. Solid understanding of mathematical modeling, probability and statistics, and the design and simulation of stochastic systems.
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Familiarity with AI algorithms, predictive modeling and machine learning techniques and their application to insurance problem solving. Proficiency in programming languages such as Python, R, and SQL.
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Utilize technical skills such as hypothesis testing, machine learning and retrieval processes to apply statistical and data mining techniques to identify trends, create figures, and analyze other relevant information.
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Technical Proficiency :Demonstrated expertise in Python, SQL, Git, and common Data Science and Machine Learning libraries. Reporting and Visualization : Build and automate comprehensive reports, develop and prototype dashboards to provide insights at scale, leveraging BI platforms (we use Looker) for clear data visualization.
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Requires one (1) year of experience in each of the following: analyzing large data sets from multiple data sources for health care industry; Python; machine learning, statistical analysis, predictive modeling; SQL programming languages; “big data” platforms including Hadoop (Azure, GCP, or AWS); designing data models and solutions for analytical and reporting use cases.
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