Data ScienceJobs
Analyze data, build predictive models, and drive business decisions with machine learning. Python, SQL, statistics, and ML frameworks required. $130k-$260k+ salaries at top AI and tech companies.
Data scientists combine statistics, programming, and domain expertise to extract insights from data and build predictive models. The role spans from exploratory analysis and A/B testing to deploying production ML models. With the rise of AI, data scientists increasingly work with large language models and generative AI applications.
Top companies hiring data scientists include AI labs, tech companies, and startups across every industry. Core skills include Python, SQL, statistical modeling, and ML frameworks like scikit-learn, PyTorch, and TensorFlow. Experience with data visualization, experiment design, and cloud platforms is highly valued.
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Frequently Asked Questions
What's the difference between a data scientist and an ML engineer?
Data scientists focus on analysis, experimentation, and model development -- they explore data, run experiments, and build prototypes. ML engineers focus on taking models to production -- they build scalable training pipelines, optimize inference, and maintain production systems. In practice, the roles overlap significantly, especially at smaller companies.
What skills do data scientists need in 2026?
Core skills include Python, SQL, statistics, and ML frameworks (scikit-learn, PyTorch). Increasingly, data scientists also need experience with LLMs, prompt engineering, and GenAI tools. Strong communication skills for presenting findings to stakeholders remain essential. Cloud platform experience (AWS, GCP) and data engineering skills (Spark, Airflow) add significant value.