- UpvoteDownvoteShare Job
- Suggest Revision
Proficiency in common geospatial software applications and tools, such as visual programming (JEMA, FADE/MIST, ECO/ETAS), Python, SQL, Git, GIMS, A WS Sagemaker, A WS Cloud, ESRI ArcGIS, statistics (descriptive, Bayesian), Markov-Chain modelling, TensorFlow, Linear Algebra, R, SAS, NLP.
ExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
- Suggest Revision
Demonstrated experience using data processing tools, such as Airflow, Spark, dbt, Fivetran, Databricks, Talend. , with two or more programming languages (Python, SQL, Java, C#, Scala, R, etc.
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.
Full-timeExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
- Suggest Revision
Experience in Text Analytics, developing different Statistical Machine Learning, Data Mining solutions to various business problems, and generating data visualizations using R, Python.
Full-timeExpandApply NowActive JobUpdated 11 days ago - UpvoteDownvoteShare Job
- Suggest Revision
Demonstrated commercial experience in data modeling, design, and development for relational databases with complex SQL (Snowflake, BigQuery, Redshift. 5 to 10 years hands-on experience developing data solutions in one or more cloud technologies (AWS, Azure, GCP, Snowflake, etc.
ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
In-depth knowledge of technical areas such as Snowflake, Python, Spark, R, Shiny, Jupyter, and associated packages and libraries (e.g., NumPy, pandas, SciPy, OpenAI). Navigate large, complex datasets for data mining, profiling, and curation, as well as utilize natural language processing (NLP) techniques.
ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Utilize Scala, Databricks, Python, Trifacta, DataRobot, and R to implement data processing and analysis tasks. Knowledgeable of technologies such as Scala, Databricks, Python, Trifacta, DataRobot, Kafka, StreamSets, and/or R programming language.
Full-timeExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
- Suggest Revision
2+ years of hands-on experience with data science and analytics, modeling platforms, data engineering software and visualization tools (e.g. Advanced SQL, PL/SQL, R, Python, SAP HANA, Spotfire, Tableau, Hadoop, Redshift.
ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
- Suggest Revision
Fluid understanding and working with data management software, geographic information systems (GIS), statistical programs (R, STATA or Python), and database query languages (SQL.
Full-timeExpandApply NowActive JobUpdated 17 days ago - UpvoteDownvoteShare Job
- Suggest Revision
Experience with Ellucian/Banner, Microsoft Power BI, SPSS, R, Python, Oracle SQL Developer, Evisions Argos, Tableau preferred. Strong proficiency in SQL, Python, or R, and experience with BI tools such as Tableau or Power BI. Demonstrated ability to translate complex datasets into clear and actionable insights.
Full-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
- Suggest Revision
We work with large datasets while ensuring data availability, integrity, and security, utilizing technologies such as SQL, Python, R and analytics tools like Looker, Tableau, and Qlik.
$110,000 - $140,000 a yearFull-timeExpandApply NowActive JobUpdated 11 days ago - UpvoteDownvoteShare Job
- Suggest Revision
Utilizing knowledge of modern big data approaches preferred: e.g. PySpark, Apache Spark, Azure Databricks, Azure SQL, Azure ML, R, Python, Java, etc. Leveraging experience with basic programming: Python, R, SQL, Matlab, C.
Full-timeExpandApply NowActive JobUpdated 28 days ago - UpvoteDownvoteShare Job
- Suggest Revision
We are seeking a highly skilled and experienced Geospatial Data Scientist with a strong background in remote sensing and image processing to join our team. You will leverage background in remote sensing, image processing, statistical, geo-statistical and machine learning models to analyze complex imagery data to develop an scalable image processing pipeline.
$75 - $85 an hourFull-timeExpandApply NowActive JobUpdated 18 days ago - UpvoteDownvoteShare Job
- Suggest Revision
Must have knowledge of advance data science methods; examples include prescriptive, cognitive algorithms, big data analytics, commercial and open source Hadoop, data-mining, Python, “R”, machine learning, or NLP.
Full-timeExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
- Suggest Revision
Proficient in data science, optimization, machine learning, Python, R, SQL, data analysis, analytical skills, teamwork, and communication skills. Bunge has an exciting opportunity available for a Principal Data Scientist.
Full-timeExpandApply NowActive JobUpdated 28 days ago
python r data processing jobs Title: data scientist sr Company: Inc
FEATURED BLOG POSTS
A Potential TikTok Ban?!
As you may already know, there has been a lot of talk lately about the possibility of a TikTok ban. While this has not yet come to fruition, it's important to consider the implications this could have for businesses and recruiters who rely on TikTok as a platform to market their brand, recruit new talent, and connect with their audience.
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.