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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, Python, Databricks and deep knowledge of Qlik, PowerBI, Tableau for visualization.
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Demonstrated proficiency with data science languages (R, Python, SQL, Julia, SAS) and visualization tools (Tableau, Spotfire, SAS, JMP, RShiny) Experience with analytic methods and technologies (artificial intelligence, machine learning/ deep learning/ neural networks, natural language processing, visualizations.
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Preferred Requirements/QualificationsMaster's or PhD degree highly preferred with 5 to 6 years of Machine Learning or Data Science experience in Technology companies, Life Sciences, Pharma or Biotech.
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Lead the engineering team in designing, developing, and deploying solutions applying modern web frameworks, machine learning solutions, data engineering technologies, microservices, and cloud-native architecture.
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In addition, the ideal applicant should have a strong programming background (e.g. Python, R, SQL, MATLAB) and the drive and enthusiasm to learn about clinical neuroscience by assisting in state-of-the art patient-centered research.
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Expertise in Python, Spark, Machine Learning, SQL, and ElasticSearch. Experience with data visualization technologies, including Vue. JS, React, or similar, and API development. Ingest and incorporate additional prospection data from HubSpot into the history, providing a more robust dataset for analysis and visualization.
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Proficient with the core concepts of at least one programming language such as Python, R, and SQL and adept with machine learning frameworks such as TensorFlow and PySpark. Accredited Artificial Intelligence (AI) / Machine Learning (ML) certifications (, AWS, Google Data Analytics, Microsoft Azure) Information for applicants with a need for accommodation: The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs.
$198,375 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience with machine learning frameworks (e.g., TensorFlow, scikit-learn) and data visualization tools (e.g., Tableau, Power BI). Stay updated on the latest developments in data science, machine learning, and real estate technology.
$220,000 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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With dependency mapping- Data analysis and data modeling- Strong experience in Python, SQL, shell scripting- Experience interacting with APIs, SFTP, Cloud Storage locations (eg. This individual will work directly with the Data Architect, along with the CTO of Lasso to establish a Machine Learning platform along with best practice engineering standards to ensure secure and successful data solutions.
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Experience overseeing teams that use a range of data tools/languages to conduct/automate analysis and derive insights (e.g., Alteryx, SQL, QGIS, Python, R, Tableau, Qlik, etc.) Machine learning, predictive modeling, and geospatial analytics.
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Typical solutions will utilize machine learning, artificial intelligence, statistical analysis, automation, optimization, and/or data visualizations. Required competency in Python and classical ML methodologies - deep Learning and Databricks experience is preferred.
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Three (3) years of experience working with relational data bases (Oracle or Microsoft SQL Server) Write and test requested reports utilizing Crystal Reports, SQL language, or other query tools.
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Analyzing structured and unstructured data using data mining/statistical/machine learning/deep learning tools, Data visualization, Digital/Web analytics tools and techniques and storytelling.
$205,000 a yearFull-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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Be responsible for the development of the conceptual, logical, and physical data models, the implementation of RDBMS, AWS Redshift Datawarehouse ,operational data store (ODS), data marts, and data lakes on target platforms (SQL/NoSQL.
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Develop tools that leverage the diverse data within our DECODE database using data mining, analytics, statistics, and machine-learning to provide efficient data slicing, integration, manipulation, visualization, and interpretation to surface novel discoveries.
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