🧠 7 Resume Tips for Data Science & ML Roles 📄✅

1️⃣ Start with a Strong Summary
⦁ Highlight skills, tools, and domain experience
⦁ Mention years of experience and key achievements

2️⃣ Showcase Projects that Matter
⦁ Focus on real-world impact, not just toy datasets
⦁ Mention metrics (e.g., “Improved accuracy by 12%”)

3️⃣ Tailor for the Role
⦁ Align keywords with the job description
⦁ Use relevant tools and models mentioned in the listing

4️⃣ Highlight Tools & Techniques
⦁ Python, SQL, Pandas, Scikit-learn, TensorFlow
⦁ Also list Git, Docker, AWS if used

5️⃣ Add Business Context
⦁ Mention how your model helped reduce costs, improve conversion, etc.
⦁ Show you understand the why behind the model

6️⃣ Keep It One Page
⦁ Concise and clean layout
⦁ Use bullet points, not long paragraphs

7️⃣ Include Public Work
⦁ GitHub, blog posts, Kaggle profile
⦁ Show you build, write, and share

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