- UpvoteDownvoteShare Job
- Suggest Revision
Data science, machine learning, optimization models, Master's degree 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.
Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Build scalable and reproducible work in Python or R including data ingestion, quality checks, cleaning, analysis, modeling, and output. 3-5 years of professional experience programming statistical analyses in SPSS, Stata, Python or R (Python and R highly preferred.
Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
The role requires expertise in programming (SAS, R, Python, SQL, or STATA) and quantitative analysis. 3+ years of experience in programming (SAS, R, Python, SQL, or STATA.
RemoteExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
- Suggest Revision
Leverage a broad set of modern technologies - including Python, R, Scala, and Spark - to analyze and gain insights within large data sets and implement systems for automatic data collection, curation and model training.
ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Expertise in Python, R, SQL, statistics, data mining. Visualize insights using Microsoft Office, Tableau, Python, R. Significant experience as a Data Scientist or advanced analytical role.
ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
O Programming Language: Python, R, SQL, Java, Scala, Pyspark/Apache Spark, Shell scripting. Use programming languages including but not limited to Python, R, SQL, Java, Scala, Pyspark/Apache Spark, Shell scripting.
ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Proficiency in ML/Data Science/Statistical Modeling languages such as Python, R to build Propensity Models, Customer Segmentation, Churn Scores, Forecast Models etc. Write sophisticated and efficient code to transform raw data sources into easily accessible models by coding across several languages and tools such as SQL, Python, Spark, Databricks, Airflow, Azure, AWS, etc.
ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
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.
ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
The ideal applicant should have a strong programming background (e.g., Python, R, SQL, SAS, and/or STATA) and the drive and enthusiasm to learn about clinical care by assisting in state-of-the-art patient-centered research.
ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Extensive experience working with healthcare data, utilizing SQl, R, Python and/or Tableau. The Senior's primary responsibility is to leverage strong technical skills (SQL, R, Python, and Tableau) and healthcare industry knowledge (payor, provider, pharmacy, public health, epidemiology, etc.
Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Proficiency with MLOps architecture tools like Docker, Kubernetes, Airflow, Kubeflow, and experience in API development within a Python environment. Proficiency in programming languages (Python, Java, Scala) and ML frameworks (TensorFlow, PyTorch, Scikit-Learn), underpinned by a solid grasp of MLOps practices, including design documentation, testing, and source code management with Git.
ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Expertise in open source data science technologies such as Python, R, Spark, SQL. 5+ years of experience using AI/ML , data science software (e.g., Python-based tools.
ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Proficiency in programming languages such as Python for data manipulation, analysis, and model development. Master’s Degree in related field (e.g., Data Science, Predictive Analytics, Machine Learning, Statistics, Applied Mathematics, Computer Science.
ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Python and/or R Programming – Machine learning/statistical methods, quantitative analysis and data modeling. 3+ years of experience programming in Python, or R. Projects will require the use of critical thinking and communication to complete, along with technical skills including Python, SQL, and PowerBI to manipulate, model, and present data.
ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
You will support R&D with single-cell and bulk RNA and DNA analysis and pipeline development while using and promoting best practices for coding (Python/R) and reproducible research.
ExpandApply NowActive JobUpdated Today
python r jobs Title: data scientist Company: Oracle
FEATURED BLOG POSTS
The Effects of Workplace Racism and Sexism
One day it's a covert statement to a mother returning to work after maternity leave. Another day it's a lingering gaze at an employee enjoying a culturally rich meal. These microaggressions (or sometimes macroaggressions) can take an employee from a confident, high-performer to one that feels insecure being themselves at work. Your employees engage with people with different ideas and feel most comfortable and valued when they can work without losing their cultural, racial, and gender identity. While most employers know this, why have workplace racism and sexism often been neglected?
When Rage Applying Strikes: How to Identify Unserious Candidates
As the job market remains highly competitive, we have seen a surge in "rage applying." This is when candidates apply to multiple jobs, often without considering whether they are truly interested in the role. Rage applying goes hand-in-hand with quiet quitting. Often, employees want to entertain the thoughts and feelings of leaving their job, but they aren't necessarily serious about leaving yet. Meanwhile, other employees engaging in this trend are actually trying to find a better role. As a recruiter, it can be hard to identify who are the real applicants in a sea full of quiet quitters, but understanding rage applying and identifying red flags will certainly help.
How to Increase Job Ad Exposure
In today's competitive job market, writing quality job ads is critical for attracting top talent to your organization. While networking and candidate referrals are prime real estate for finding qualified candidates, nothing beats the tried-and-true method of writing an extraordinary job ad. But while writing a great job ad is the first step, what's more important is increasing visibility. You could have the most detailed, well-written ad on the internet, but if no one sees it, then you are wasting time (and potentially money!). Employers often believe that job boards are the root of the problem, but you can learn how to increase job ad exposure by tweaking a few steps of your recruitment process.
How to Navigate Hiring Out of State
The job market has shifted significantly in recent years. The accelerated adoption of technology has not only pushed many companies into remote working arrangements but also increased the availability of supporting tools and technologies (i.e., video conferencing and collaboration software).
Building a Candidate Pipeline Through Internships
Building a candidate pipeline through a great internship program for local college students and recent graduates at local universities is a great and cost-effective way to attract and retain top talent. By offering meaningful and impactful work experiences, regular feedback, coaching, and mentorship, you can create a positive internship experience that will make your organization a sought-after destination for future employees. This not only benefits the organization in the short-term but also in the long-term, as you'll have a pool of well-trained and experienced candidates who may be interested in full-time employment once they graduate. Furthermore, building relationships with local universities and college students can increase brand awareness and build a positive reputation for your organization in the local community.
Hiring Transparency
Transparency in hiring refers to the open and honest communication and information sharing that takes place between employers and job candidates. It encompasses all aspects of the hiring process, from posting job descriptions to providing feedback on performance during and after the interview process. In today's job market, hiring transparency has become increasingly important for both employers and candidates alike.
Recruitment strategies that are weird, but actually work
In the current candidate-driven job market, recruiters are looking for unique ways to attract talent. Some have resorted to even (dare we say it?) recruitment strategies on the border of weird and wacky. What can we learn from the unusual recruitment tactics that are being used and actually getting results? Here’s a rundown of some unique recruitment strategies that actually work.