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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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This role will coordinate with our hardware team to improve data collection from our novel spectral soil probe for building machine learning models, will partner with our soil science team to collect and analyze soil and geospatial data sets, and will collaborate with our business development team to accurately and effectively communicate soil carbon results to our customers.
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Requirements: Requires a Bachelor’s degree or foreign equivalent in Computer Science, Electronic Engineering, Information Technology, or related field and 5 years of progressively responsible, post-baccalaureate experience as a Computer Programmer, Application Development Lead, Developer or related position involving Domain experience in Banking and Finance.
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Superior writing, editing, design, data visualization, videography, or photography skills; experience coordinating with stakeholders and juggling multiple projects; demonstrated ability to execute advanced data visualization techniques such as interactive dashboards (Tableau) or geographic information systems ( ESRI /ArcMap.
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Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.
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An Advanced Degree (or equivalent knowledge/training) in Bioinformatics, Computer Science, Data Science, or related field. A Bachelor’s Degree (or equivalent knowledge/training) in Bioinformatics, Computer Science, Data Science, or related field and a minimum of 8 years of demonstrated success implementing and maintaining large scale genome sequence data analysis systems with large complex technological programs or an equivalent combination of education and experience.
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The successful candidate will work collaboratively with leading researchers from the Institutes of Science (IOS), our technology hubs, and members of the Institute of Medicine (IoM) to think strategically, lead and execute preclinicalresearch to generate decisional data packages in support of drug-discovery stage projects.
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We combine expertise across multiple fields: high-performance scientific computing, physics-based modeling and simulation, data science, machine learning, applied mathematics, optimization, statistics, decision support, data analysis and visualization, computer systems architecture, quantum computing, neuromorphic computing, human-technology connections, and others.
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A proven track record of administration, engineering, and operationalizing Databricks platform in a production mode at scale for Data Engineering, Data Science or MLOps use cases. As an AWS Databricks Administrator within this Data Services team, you will be putting your Databricks knowledge and experience to work as you collaborate with teams of Data Engineers, Infrastructure and Product Managers to build and maintain the new data infrastructure platform for all of Live Nation and Ticketmaster.
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Knowledge and exposures to Azure SQL Data Warehouse, Databricks or other cloud or on premises MPP data warehousing systems (SAP HANA, Teradata, Snowflake). The experience should be with requirements gathering, SQL, Data Integration tools such as Informatica PowerCenter, Microsoft SSIS, Azure ADF and Data Warehousing techniques.
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Menlo Park, California (hybrid role with 2 days a week onsite) or 100% remoteIn data science or related field, expertise in R or Python, understanding of statistics and machine learning techniques, experience in harmonizing data models and working with real-world healthcare dataResponsibilities: Develop standardized data models, link and process data, generate regulatory-grade RWE, collaborate with diverse teams.
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As a part of the global research, our AI research in Silicon Valley focuses on Foundation Models, Big Data Visual Analytics, Explainable AI (XAI), Natural Language Processing, 3D Perception & Mixed Reality, Cloud Robotics, Data Science, AI Platform, Time-series Analysis.
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Experience with Data Warehouses (BigQuery, Snowflake, etc.) Collaborate with Technical Lead, fellow engineers, Product Managers, QA, and TechOps to develop, test, secure, iterate, and scale complex data infrastructure, data models, data pipelines, APIs and application backend functionality.
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College or university with specialization in one or more appropriate disciplines in agricultural science, biological science, chemical science, physical science, mathematics, and/or statistics, including the completion of college level courses in both Botany and Entomology.
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PhD in life science-related fields (Immunology, Molecular Biology, Pharmacology, Chemistry, and Biochemistry) or Master’s with 6+ years in science-related fields. Record experimental procedures, observation, and analyze data accurately.
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data science mining jobs in California, MO
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