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We want Data Science/Machine learning/Data Analyst and Java Full stack candidates. For data Science/Data Analyst/AI/Machine learning Positions. Currently, We are looking for entry-level software programmers, Java Full stack developers, Python/Java developers, Data analysts/ Data Scientists, Machine Learning engineers for full time positions with clients.
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Experience with statistical modeling, machine learning, deep learning or data mining concepts, and a track record of solving problems with these methods. Develop solutions focused on data science and engineering using machine learning, deep learning algorithms, statistical concepts, data modeling, software development and visualizations.
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The Data Scientist interprets and analyzes data to solve problems and sponsor needs, utilizing advanced algorithms in statistics, machine learning, and artificial intelligence for analyzing and classifying datasets.
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Significant experience applying one or more of the following research methods: regression (preferably mixed models), data classification and reduction (cluster, factor, principal components, decision trees), Bayesian inference or other advanced machine learning techniques.
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Drive both short term and long-term research initiatives in areas such as artificial intelligence, machine learning & data mining, natural language processing, bigdata systems, information and data visualization, social & cognitive science.
$345,200 a yearFull-timeExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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Reporting to the Lead Data Scientist, you will play a crucial role in our analytics capabilities, spearheading the development and implementation of cutting-edge machine learning and artificial intelligence frameworks that empower our customers to unlock actionable insights from complex data.
$161,800 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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We are interested in a variety of topics including data visualization and interactivity, applied machine learning and AI, AI bias and trust, big graphs, natural language processing, data mining, big data management, and heterogenous data analytics.
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Gather and utilize geologic mapping, drill data, hydrologic information, quality testing results, topography, aerial photography, survey data, sales forecasts, and other mine planning data to design 3-D mine plans and mining/stripping schedules.
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5+ years of experience in data analysis or data science, with 3+ years focusing on machine learning problems, ideally in a relevant space (KYC, sanctions detection, anti-fraud detection, treasury management, crypto/blockchain data science.
$195,000 a yearFull-timeExpandApply NowActive JobUpdated 24 days ago - UpvoteDownvoteShare Job
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The Machine Learning Engineer role requires experience in Azure OpenAI, Large Language Models (LLMs), Python, and proficiency in developing applications using Streamlit, LangChain, Databricks, and Python frameworks like Flask and FastAPI. The ideal candidate will be adept at building scalable machine learning models and deploying them to production environments, and also being part of customer success teams.
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2+ years of relevant experience in developing and deploying large scale machine learning or deep learning models and/or systems into production, including batch and real-time data processing, model containerization, CI/CD pipelines, API development, model training and productionizing ML models.
$223,600 a yearFull-timeExpandApply NowActive JobUpdated 21 days ago - UpvoteDownvoteShare Job
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The Machine Learning Engineer will be responsible for architectural design and planning, advanced data pipelines, model integration and optimization, scalability, performance and research and innovation supporting production AI systems.
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Works closely with the data science and business intelligence teams to develop data models and pipelines for research, reporting, and machine learning. Norfolk Southern Corporation is currently seeking a Senior Big Data Engineer with an affinity for working with others to create successful solutions.
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6+ years of experience in in data mining, statistical analysis, auditing, and/or forecasting. 65% - Data Analytics - Analyzes large volumes of data and leverages data analytics tools to create new dashboards, reports and any additional ad-hoc requests, using a wide variety of database applications / analytical tools /languages including GCP BigQuery, SQL, SAS, R, Python, Jupyter Notebook, Adobe Analytics, and Tableau.
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Design, Develop and implement data science projects, including machine learning models, deep learning models, NLP solutions, statistical analysis, and data visualization.
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big data mining machine learning jobs Title: scientist Company: Ehs Technologies in Atlanta, GA
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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.
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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.