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Remote Data Science Jobs: 5 High-Demand Roles for Career Growth

Data Science Dojo

Key Skills Proficiency in SQL is essential, along with experience in data visualization tools such as Tableau or Power BI. Strong analytical skills and the ability to work with large datasets are critical, as is familiarity with data modeling and ETL processes. This role builds a foundation for specialization.

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Ask HN: Who wants to be hired? (July 2025)

Hacker News

NET, Typescript / Javascript (inc Node), React, Vue, Laravel (php) SQL (t-SQL mostly) Unity (as a hobby) Azure Management (pretty much every major product in Azure) some exp in AWS as well and doing Salesforce (apex) integrations. Familiar with cloud systems administration on AWS, GCP, and Azure. CCNA, SCSA, MCP.

Python 54
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Ask HN: Who is hiring? (July 2025)

Hacker News

You will mostly work with Python and a range of ML frameworks such as TensorFlow, PyTorch, or HuggingFace Transformers to solve hard Machine Learning tasks and help bring these application into production by building data pipelines and cloud infrastructure on all of the major cloud providers (GCP, AWS, Azure). departments%5B%5D=.

Python 73
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Transform your data into insights: The data analyst’s guide to Power BI

Data Science Dojo

Data is an essential component of any business, and it is the role of a data analyst to make sense of it all. Power BI is a powerful data visualization tool that helps them turn raw data into meaningful insights and actionable decisions. A data analyst is a professional who uses data to inform business decisions.

Power BI 222
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Beyond data: Cloud analytics mastery for business brilliance

Dataconomy

Key features of cloud analytics solutions include: Data models , Processing applications, and Analytics models. Data models help visualize and organize data, processing applications handle large datasets efficiently, and analytics models aid in understanding complex data sets, laying the foundation for business intelligence.

Analytics 203
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The Data Dilemma: Exploring the Key Differences Between Data Science and Data Engineering

Pickl AI

Unfolding the difference between data engineer, data scientist, and data analyst. Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. Data Modeling: Entity-Relationship (ER) diagrams, data normalization, etc.

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5 Reasons Why SQL is Still the Most Accessible Language for New Data Scientists

ODSC - Open Data Science

For budding data scientists and data analysts, there are mountains of information about why you should learn R over Python and the other way around. Though both are great to learn, what gets left out of the conversation is a simple yet powerful programming language that everyone in the data science world can agree on, SQL.

SQL 98