- UpvoteDownvoteShare Job
- Suggest Revision
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.
RemoteExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
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.
RemoteExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
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.
RemoteExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
Data Scientist (Healthcare) 100% Remote. Data Science & Machine Learning Frameworks. Python (for preprocessing, data analysis, machine learning, scripting) Data Governance & Security.
RemoteExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
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.
RemoteExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
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.
RemoteExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
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.
RemoteExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
TensorFlow, PyTorch, Keras (for deep learning and complex machine learning, including neural networks and advanced AI) ETL Tools (e.g., Informatica, Talend, AWS Glue) AWS SageMaker (for end-to-end machine learning development, training and scalable machine learning in a managed cloud enviornment.
RemoteExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
Bachelors Degree computer science, artificial intelligence, informatics or closely related field. AWS Bedrock (for accessing pre-trained LLMs and foundation models without managing infrastructure) Experience with Epic or Cerner (popular EHR systems in healthcare.
RemoteExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
AWS, Google Cloud, or Azure (cloud platforms for scalable computing) SQL-based Databases (e.g., PostgreSQL, MySQL, Microsoft SQL Server) ICD-10 Coding (for medical diagnosis and procedure classification.
RemoteExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
HL7 (Health Level Seven International standards for electronic health information exchange) Electronic Health Records (EHR) Systems. Predictive Modeling (for patient outcomes, risk analysis) NoSQL Databases (e.g., MongoDB, Cassandra.
RemoteExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
The successful candidate will have demonstrated competence in developing highly scalable artificial intelligence systems with multiple dependencies across teams. R (for statistical computing and bioinformatics.
RemoteExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
CI/CD Pipelines (for automating deployment and monitoring of machine learning models) MATLAB (for algorithm development, though less common in healthcare) Experience with machine learning and statistical analyses are needed.
RemoteExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
AWS Lambda and Step Functions (serverless computing and workflow automation) Dimensionality Reduction (e.g., Principal Component Analysis (PCA), Cloud Computing & DevOps Skills. A/B Testing (for clinical trials or health interventions.
RemoteExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
Time Series Analysis (useful for patient monitoring, trend analysis) Descriptive Statistical tests (correlaton, covariance, chi-square, univariate, multivariate analyses) Scikit-Learn (for classical machine learning.
RemoteExpandApply NowActive JobUpdated Yesterday
big data jobs Company: Experian in Hurricane, France
FEATURED BLOG POSTS
10 Importancies of Setting Realistic Goals
We’ve all heard how important it is to set professional and personal goals. Developing and establishing goals keeps us motivated and moving forward in life. But not all goals are created equal. If you’re chasing goals that are too lofty, you’ll end up disappointed when you cannot reach them. Setting goals that are achievable and measurable is the key to success.
Email Etiquette Principles - Why is it Important
Why is email etiquette important? Let's imagine you're hiring for a new role, and you’ve just received the email below.
10 Reasons HR is Important to an Organization
"Nothing we do is more important than hiring and developing people."
7 Importances of Organizational Culture and How to Build It
The world of work has drastically changed in the past few years. Where a good salary and a nice office might have been enough to attract talent in the past, employees today expect flexibility, growth opportunities, and a healthy work environment. In fact, 77% of applicants say they’d consider a company’s culture before applying for a job.
Collaborative Recruiting: The Key to a Better Talent Acquisition Strategy
Talent acquisition is a multi-stage process where candidates undergo various application steps before getting hired. The unfortunate reality is that it is a labor-intense system, with the hiring manager and recruiter often handling all of the work on their own. Ask any one of them, and you will hear about the overabundance of applications and the demanding task of filtering through them to find the best candidates. The quality of talent suffers under the weight of all that work on one person's hands. It's not easy, but as many companies are starting to realize, there is a better way. The future of talent acquisition lies in collaborative recruiting!
Why is it so Hard to Get a Job After College
For many, it was easy finding a job while in college. But after job hunting for weeks, you may wonder why it is so hard to get a job after college. After all, you’ve put a lot of time and effort into getting your degree. But don’t get discouraged. The University of Washington found that 53% of graduates are either unemployed or working a job that doesn’t require a degree. Other studies also show that landing your first job can take between 3 and 6 months. So, getting your first job takes time.
Making the Move to Salary Transparency
The salary transparency trend continues. Last year, Colorado passed its Equal Pay Transparency Rules, which required employers to include compensation in job postings, notify employees about promotional opportunities, and record job descriptions and wage records. Soon after, states like Washington, Nevada, Maryland, and Rhode Island followed suit.