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Drive business impact by identifying and acquiring or mining data from multiple and diverse sources for actionable insights (including digital session web data, Salesforce and other CRM/CDP/IAM platforms, Google Analytics and Google BigQuery, etc.
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This position will manage a team of Analytics Developers, ETL Architects, DBAs and Data Scientists and is responsible for the design, development, and project management of Analytics solutions, including but not limited to building, enhancing and supporting data warehouses, Data Marts - both on prem and in the Cloud, support Epic Cognitive computing data models and develop and support predictive analytics.
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The Engineer will be working closely with data scientists, data mining experts, and business partner supporting the design of experiments and analytics, data sampling and mining, verification of data quality and information integrity, and best practices around the development and deployment of predictive/prescriptive models, DevOps operational systems and practices, and data visualization solutions.
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This high performing team works with clients to implement the full spectrum of data analytics and data science, from data querying and data wrangling, to data visualization and dashboarding, to predictive analytics, machine learning, and artificial intelligence as well as robotic process automation (RPA.
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This role will join a team developing the next generation of autonomous driving solutions drawing on state of the art technologies including big data analytics, cloud, agile and automation, for solving business problems in the automotive and next-gen mobility industry.
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A highly motivated individual, the Senior Principal Scientist will focus on strategic development and implementation of novel data science and predictive analytics methodologies to support clinical drug development.
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Predictive Security Analytics, User & Entity Behavior Analytics, Actionable Risk Intelligence, Insider Threat Prevention, Identity Analytics, Security Intelligence, Behavior Analytics, Fraud Analytics, Cloud Security Analytics, Account Compromise, Data Exfiltration, SIEM, and Security information and event management.
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Experience with data analytics (e.g. descriptive statistics, predictive modeling, data visualization), and this can include significant academic projects. Provide support for multidisciplinary study teams and perform study planning, coordination of modeling and simulation tasks, evaluation of study results, evaluation of contractor detailed designs, data extraction and analysis, and briefing to senior program leadership.
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Practical experience in delivering projects in Data and Analytics, Instrumentation, Measurement, Data Collection, Big Data, Data Warehousing, Business Intelligence.
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Understanding of analytical and insight generation approaches in the biopharma industry including descriptive and predictive analytics, business intelligence and reporting, primary market research and competitive intelligence.
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Our current analytics toolkit consists of DOMO and dbt running on top of a Snowflake data warehouse. Comfortable working with multi-TB cloud data warehouses (Snowflake*, Big Query, Redshift.
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We are seeking experienced individuals to lead client projects with the development and implementation of data-driven advanced predictive models including population risk stratification, data mining and providing overall strategic insights to assist clients achieve their vision.
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Requirements: Requires a Masters degree (or foreign equivalent), in Statistics, Business Analytics, or related field and 2 years of experience as Data Analyst, Statistical Analyst, Data Scientist, Pricing Analyst, Predictive Analyst, Modeler, Lead Consultant or related position performing Big Data Analytics.
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Experience with cloud and big data technologies to extract and analyze data (Snowflake, S3, Redshift, Athena, Hive, BigQuery, Spark, etc). Familiarity with housing and economic datasets a strong plus (i.e. demographic data such as Census, Claritas and economic time series data such as provided by Moody's Analytics and micro data such as IPUMS and other loan-level mortgage databases.
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Implementing data science and statistical tactics such as regression, time series modeling, and other predictive modeling to forecast key business metrics and build alerting to spot areas of risk early.
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big data mining predictive analytics jobs Title: analytics
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