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An excellent career opportunity is currently available for a Sr. RD Scientific Programmer within Honeywell UOP’s R&D Data Transformation and Testing Group located in Des Plaines, IL. This position will involve the development, implementation, and support of data systems along with multivariate analysis applications leading AI efforts across R&D.
$171,000 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Expertise in Python, R, SQL, statistics, data mining. Visualize insights using Microsoft Office, Tableau, Python, R. If you have a passion for data science and want to apply your skills to impactful projects at scale, we want to hear from you.
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Evaluate model performance by applying data science and math. BS or MS in Computer Science, Statistics, Mathematics, Physics or a quantitative field. In this role, you will conduct sophisticated data analytics, data mining, exploratory analysis, predictive analysis, and statistical analysis.
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Experience must include two (2) years of experience in data mining and development of ETL processes; distributed data architectures and big data processing technologies such as Spark, EMR, Hadoop and Hive; and Realtime Frameworks, collection, and processing Realtime data using kinesis Data Streams, KCL, KDA and Firehoses.
$183,855 a yearExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience writing code for data processing and engineering modeling in Python and SQL, visualization programs like Power BI. Currently pursuing a Bachelor’s degree in Computer Science, Statistics, Data Science/Analytics, Management Information Systems, Mathematics, Natural Science, Economics, Engineering or similar quantitative field and no experience and will obtain degree prior to first day of employment.
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Desired Background PhD in Computer Science or related field 4-8 years of professional experience with relevant experience building and designing distributed data systems Knowledge of statistics, data science, AI/machine learning, big data management Strong proficiency in Python and an additional language (e.g., C.
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Extended experience with tools such as Snowflake, dbt, Microsoft Power BI, Python, SQL Server, Elasticsearch, Kibana, Grafana, etc. You will bring a strong skillset in some of our most used tools: Snowflake, Power BI, dbt, GitLab, Python, and SQL. You’ll put these tools to good use in developing predictive models and analytics, designing and delivering information that excels in good storytelling, and generating impactful information for customers and your RQ colleagues.
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Proficient in R/Python, SQL, Tableau, and advanced Excel (VBA preferred). FIELD(S) OF STUDY: Data Analytics/Business Intelligence, Computer Science, Business Administration, Industrial Engineering, Mathematics, or related field.
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The Data Science & Machine Learning Engineer will be responsible for developing state-of-the-art data processing pipelines based on machine learning models and leveraging data science algorithms to parse substantial data and logs in a timely manner to automatically tackle issues or provide recommendations for the next step of solving problems.
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Apache Hadoop or Apache Spark (for big data processing) Natural Language Processing (NLP) Tools and Frameworks (e.g., Hugging Face, AWS Comprehend Medical for extracting insights from clinical text data.
$75 an hourRemoteExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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Required skills include (3 years exp in): Python or R; Tableau or PowerBI; data analytics; predictive analytics; and (2 years exp in): Machine Learning or Artificial Intelligence software development/software engineering in Azure.
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Expertise with Google Cloud Platform’s distributed Machine Learning, Data Science and Data Engineering tools (e.g. BigQuery ML, VertexAI, AutoML, Docker, Kubernetes, Kubeflow, Dataproc.
$140,000 a yearFull-timeExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Advanced and hands on experience using: Python, Databricks, Azure ML, Azure Cognitive Service, Ads Data Hub, BIQuery, SAS, R, SQL, PySpark, Numpy, Pandas, Scikit Learn, TensorFlow, PyTorch, AutoTS, Prophet, NLTK.
$140,000 - $150,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Utilize R & Python, including experience with web-app frameworks such as R Shiny & Flask. utilizing R & Python, including experience with web-app frameworks such as R Shiny &/or Flask.
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Proficiency in programming languages such as Python, R, or SQL. Strong knowledge of machine learning techniques, statistical analysis, and data visualization tools Tableau, Power BI.
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Virtual Reality Job Interviews
With the advent of desktop computers, the arduous task of scouring through weekly job classifieds became a thing of the past. The mid-1990s brought about a new era where job seekers could easily search and apply for jobs online. The introduction of AOL's Instant Messaging feature provided an even faster means for employers and candidates to communicate and schedule interviews. As smartphones became more pervasive in the early 2000s, hiring managers increasingly used phone calls for screening and interviewing candidates. Despite this trend, over 80% of interviews still took place in person.
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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.
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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?
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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.
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