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Extensive experience or knowledge of data visualization technologies such as Tableau, Power BI, Qlik and Spotfire. Experience with data modeling, data prep and machine learning tools like Alteryx, RapidMinder, RStudio and Tableau Prep.
$120,000 - $210,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Understanding of data modeling/visualization, database design principles, and data governance practices. The Decision Support Analyst will help design and implement decision-support tools and systems, focusing on advanced data analysis, modeling, and innovative data tool creation.
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Familiarity with artificial intelligence, machine learning, data aggregation and curation, data visualization, statistical analysis, and modeling tools. As the lead on data strategy, utilization of analytical modeling capabilities, and visualization efforts, close partnership with leadership and stakeholders is crucial to ensuring seamless integration of capabilities to support key decisions by providing reliable business insight in alignment with stakeholders.
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Experience deploying enterprise-wide reporting solutions while leveraging data visualization best practices. In depth knowledge of modern data technologies including Snowflake, RedShift, Azure SQL/Synaspe, Databricks or similar technologies.
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Experience with big data technologies (e.g., Databricks, Snowflake) and data visualization tools (e.g., Qlik Sense, D3. Strong knowledge in: Regression, Classification, Machine Vision, Natural Language Processing, Deep Learning and Statistical modeling.
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Expertise with data visualization tools such as Spotfire, Tableau, RShinyApp or Python Dash. Provides data engineering and programming support to Client projects, including data visualization, data mining.
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Five ( 5 ) years of related work experience to include SQL, Data Modeling , and Data Visualization Tools (Power BI). Three ( 3 ) years of related work experience to include SQL, Data Modeling , and Data Visualization Tools (Power BI.
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Proficient working experience in data collection (e.g., API, web scraping), data processing, data modeling, data integration (e.g., end-to-end ETL pipelines), and database / data warehouse management (e.g., with Databricks / Snowflake.
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The Data Scientist in this role is responsible for statistical analysis, deep learning modeling, data wrangling, mathematics algorithms, computer vision models, visualization of data and outcome, and validations of model performance.
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Providing technical support for well drilling, wellhead protection, water rights, geologic and hydrogeologic investigations, hydrogeologic testing, geologic and hydrogeologic visualization, analytical and numerical groundwater flow modeling, contaminated sites investigations, and development of conceptual site models.
$105,000 - $135,000 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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The Senior Data Engineer is a key contributor in the EDA team, providing expertise in modeling data structures and designing, building, and optimizing data mappings. Experience with at least one Data Integration tool on the level of Dell Boomi, DataStage, or Informatica.
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Min 4 years of experience as a Data Scientist in the ad-tech industry, including the following experience in: business intelligence, data mining, analytics, and statistical modeling disciplines.
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This role will serve as a hands-on contributor and be a thought leader in the areas of data engineering, cloud data strategy, Business Intelligence, Data Modeling and ETL/ELT.
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Conduct extensive collections and analytic modeling, data processing, data mining, and visualization. Proficient in common geospatial software applications and tools, such as visual programming (JEMA, FADE/MIST, ECO/ETAS), Python, SQL, Git, GIMS, AWS Sagemaker, AWS Cloud, ESRI ArcGIS, statistics (descriptive, Bayesian), Markov-Chain modeling, TensorFlow, Linear Algebra, R, SAS, NLP.
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Strong people management skills, experience in data analysis and visualization tools, proficiency in data modeling and manipulation, knowledge of statistical analysis techniques, understanding of data governance principles, business acumen, confident communication and presentation skills, ability to work in a fast-paced environment People Management Snowflake.
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