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What are the commonly utilized tools and platforms in lead engineer positions in data science, and how can I develop competency in using them?

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Lead engineers in data science commonly use tools like Python, R, and SQL for coding and data manipulation. Platforms like Apache Spark, Hadoop, and cloud services are crucial for scalable data processing. Gain proficiency by practicing coding regularly, working on real-world projects, and exploring online resources. Learn from documentation, tutorials, and engage with the data science community. Seek mentorship, attend workshops, and continuously apply these tools to deepen your expertise as a lead engineer in data science.

If you are interested in getting into this field, then check out the below video about Raghuraman. How  he was promoted to a Lead Engineer role with a good salary hike just after completing Intellipaat's Advanced Certification in Data Science and AI.

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