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Experience building and managing production-grade data pipelines using tools such as Airflow, dbt, DataHub, MLFlow. Youll be part of a close-knit team of data engineers developing and maintaining a data platform built with automation and self-service in mind to support analytics and machine learning data products for the next generation of our T3 Fleet that enable end-users to track, monitor and manage the health of their connected vehicles and deployed assets.
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Experience leveraging complex data to drive business decisions, hands on experience in data science methodologies (predictive analytics, machine learning, patient level data triggers) using R, Pytong, Databricks and deep knowledge of Qlik, PowerBI, Tableau for visualization.
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Experience with digital data from ad serving platforms (e.g. Google Campaign Manager, Other adservers), campaign planning tools (e.g. Prisma, Lumina, MediaOcean), website analytics software (e.g. Adobe Analytics, Google Analytics), paid search engine marketing data sources (e.g. Adwords, Marin.
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Apply Environmental Sequence Stratigraphic (ESS) methodology to complex data sets consisting of lithologic borings, down hole, and surficial geophysical data (including but not limited to Nuclear Magnetic Resonance, Gamma and e-logs, Electrical Conductivity/Hydraulic Profiling Tool, Seismic, and ground penetrating radar.
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Your expertise is needed on our Finance Team to collect and manage project data in compliance with Department of Treasury’s Community Development Financial Institutions Fund (CDFI Fund) program requirements, including all CDFI programs (FA, NMTC, CMF, ERP, etc.
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Alteryx, Banking, Business, Critical Thinking, Data Acquisition, Data Analysis, Data Management, Data Operations, Data Quality, Decision Making, Financial Products, Leadership, Management Reporting, Microsoft Power BI, People Management.
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Experience with deep learning, data science, and NVIDIA GPUs. Expertise in two or more data estate workloads like Microsoft’s Data & AI Platform (Azure Synapse Analytics, Azure Databricks, CosmosDB, Azure SQL, HDInsight, etc.
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Propose new database architecture and support data migration from an existing Legacy system to a new structureCreate source-to-target mapping documents to transform the source data into the target warehouse and test final transformations.
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Knowledge of Statistics, Gen AI, LLM, Python, Computer Vision, data visualization tools. We want Data Science/Machine learning/Data Analyst and Java Full stack candidates. Currently, We are looking for entry-level software programmers, Java full-stack developers, Python/Java developers, Data analysts/ Data Scientists, and Machine Learning engineers for full-time positions with clients.
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The Far Horizons program is currently doing fieldwork using two main instrument sets designed and built at the Adler: the GONet camera system, which collects all-sky nighttime environment data in the field, and the NITELite system, which is a high-altitude balloon-borne camera system that collects regional scale night-time images from the stratosphere.
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Experience with Data Ops (VPCs, cluster management, permissions, Databricks configurations, Terraform) in Cloud Computing environments (e.g., AWS, Azure, GCP) and associated cloud data platforms, cloud data warehouse technologies (Snowflake/Redshift), and Advanced Analytical platforms (e.g., Dataiku and Databricks.
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The Associate Director, Analytics Enablement supports the collection and activation of analytics data across RAPP client projects, providing technical solutions to fulfill measurement and reporting goals.
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PMO lead for onboarding and embedding an ESG Tool, including Carbon Accounting – data sources, aggregation, formatting; process framework and data input controls, change management to embed into ways of workingAssist to design and embed a cost model covering revenue, GP, overhead, fixed costs, and EBITDA to provide multiyear revenue and EBITDA projections to support Sustainability CAPEX/OPEX investments and realize Sustainability Strategy / timely regulatory compliance.
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Embedded within Tempus as an onsite researcher, the postdoctoral fellow will have direct access to over 150k de-identified samples with genomic and clinical data, a large organoid repository with genomic and pharmacological screening data, a huge computational environment, and mentorship and collaboration from clinicians, molecular biologists, and data scientists.
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Data Warehouse: Azure Databricks, Snowflake. Prior data visualization experience required (Power BI, Tableau, Looker, etc. Data Science: Azure Databricks. Create data mappings to document technical lineage of data from source systems through to analytics products.
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data job Company: Hi Line in Chicago, IL
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