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Apache Hadoop or Apache Spark (for big data processing) Data Warehousing (e.g., AWS Redshift, Google BigQuery) Natural Language Processing (NLP) Tools and Frameworks (e.g., Hugging Face, AWS Comprehend Medical for extracting insights from clinical text data.
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Docker, Kubernetes, ECS, EKS or AWS Fargate (for containerization and orchestration of data applications and reproducibility) Data Visualization Tools (e.g., Tableau, Power BI, Plotly) The Data Scientist will be responsible for driving insights from the vast amounts of patient and environmental data available within our data warehouse.
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HIPAA Compliance (handling sensitive patient data securely) Data Privacy (understanding of privacy laws such as HIPAA, GDPR) Work closely with researcher teams to design analysis specifications, including input data specifications, data cleaning, algorithms, and interpretation of results.
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Data Scientist (Healthcare) 100% Remote. Data Science & Machine Learning Frameworks. Python (for preprocessing, data analysis, machine learning, scripting) Data Governance & Security.
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Develop and implement algorithms on existing data warehouse records and identify new external data sources to be ingested to the data warehouse to strengthen analyses. Research and implement AI algorithms, apply off-the-shelf AI and data-centric tools, and collect, store, and maintain data.
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Developing scalable, efficient, and cost-effective data solutions leveraging AWS technologies and big data tools like Databricks, Airflow, and Dremio. Proven experience as a Data Engineer, Data Reliability Engineer, or in a similar role in an SRE environment.
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Auditing & Compliance Tools (for ensuring secure and compliant data handling) SAS (common in healthcare data analysis) Data Anonymization or De-identification techniques (for research and compliance.
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XGBoost or LightGBM (for gradient boosting in structured data) Data Tools & Platforms. Clinical Terminologies (e.g., SNOMED, LOINC) Natural Language Processing (NLP) (for analyzing clinical notes or electronic health records.
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Architect and implement big data processing solutions using Databricks, leveraging Apache Spark for data transformation, ETL processes, and machine learning workflows. Proficiency in Databricks, Apache Spark, and related big data technologies.
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6+ years of experience in data engineering working with big data systems that can process and transform data at scale. Experience developing with data SaaS and BI tooling (Fivetran, Looker, dbt, Databricks, Apache Airflow, etc.
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Subcategory Big Data Engineer. Data Management Analysts (Data Management, Data Governance, Data Quality, Test Data Management, Data Architecture, Data Security, Programing (SQL, JAVA, Python, R), Data Analysis Software (e.g., Excel, SAS, SPSS), Knowledge of Database Query Language (e.g., SQL), Report Creation and Data Visualization (Tableau and R Studio) , Understanding of Statistical Methods and Techniques to Analyze Data.
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We’re helping patients get the best care possible by working on digital health experience, analyzing big data to streamline the delivery of care, and reaching out to medically complex patients to better understand their needs.
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As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
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Human-Centered Data Science (e.g., databases, big data, information retrieval, robotics, artificial intelligence, information visualization) Cultural Heritage Informatics (e.g., archives, digital collections, preservation, digital curation, digital humanities, museum studies, metadata, cultural studies of information technology, history of information, critical data studies.
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Plant monitoring and care during vegetative and flowering phase: trimming and staking; big leafing and pruning; plant care, watering and feeding; plant monitoring and climate control; pest and disease control; inventory data input.
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big data jobs Title: payroll manager Company: Verizon in NJ, Germany
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The Best Remote Jobs: Where & How to Find Them
The Covid-19 pandemic hasn’t been easy on any of us, but if there’s one silver lining, it’s the fact that remote work has grown in popularity because of it. Companies that previously weren’t open to their employees working remotely were suddenly forced into allowing it. Since then, they've realized that much of their workforce is happier and more productive. Naturally, this has led to more remote job openings, which is great if you’re interested in this type of position. Read on to learn more about the best remote jobs and where to find them.
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Learning to recruit passive candidates is a different ballgame than recruiting active ones. While an active candidate is someone who is currently looking for a new job, a passive candidate tends to be the opposite. Passive candidates are either already working or not looking to work. So, instead of these candidates coming to you, you'll have to find them and reach out to them first.
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Today, hiring and retaining talent looks much different than it did only two or three years ago. Financial instability and the strain on our mental health brought on by the pandemic has made everyone more wary and selective of their workplace and employer. Whereas in the past people might have prioritized promotions and financial reward, today they look at other factors such as workplace flexibility, personal fulfillment and values alignment.
How Many Hours is Part-Time vs. Full-Time Work?
Growing up you watched your parents shuffle to and from the office, held hostage to their 9 to 5. If jammed-packed schedules and deadlines sound frightening, you might consider pivoting your search to part-time jobs. In fact, even employers have shifted their preference, selecting more people open to the idea of flexible working hours.