AI/ML Data Analyst-Node JS, Python, SQL (Hyderabad)
Cortex Consultants
Job description
Job Title: AI/ML Data Analyst Location: Hyderabad, India Experience: 3-6 years Employment Type: Full-time Working Style: Hybrid The Chance: We are seeking a highly skilled AI/ML Data Analyst to develop and deploy machine learning models, optimize data pipelines, and drive AI-driven innovation. The ideal candidate will have expertise in machine learning, artificial intelligence, automation, and data engineering, along with hands-on experience in Node JS,Python, SQL, and data scraping along with experience working with structured and unstructured data. This role requires a strong analytical mindset, problem-solving abilities, and the ability to work with large datasets to drive impactful business solutions. What You Will Do:
- Develop and deploy machine learning models for predictive analytics and automation.
- Build and optimize data pipelines using SQL, Python, to process large datasets efficiently.
- Implement data scraping techniques to extract and preprocess structured/unstructured data from various sources.
- Work on AI-powered automation to streamline internal workflows and enhance data-driven decision-making.
- Collaborate with data engineers and product teams to integrate AI/ML solutions into existing systems.
- Optimize model performance and ensure scalability for real-world applications.
- Stay updated with the latest advancements in AI, ML, and data engineering. What You’ll Need to Succeed:
- Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or a related field.
- 3-6 years of relevant experience with a SaaS or IT Product Development company.
- Proficiency in Data Analysis leveraging NodeJS and Python, including libraries such as TensorFlow, PyTorch, Pandas, and Scikit-learn.
- Experience with AI-based Python notebooks such as Databricks, Snowflake, Hex, or Jupyter
- Experience with data interrogation techniques using technologies such as GenAI, BeautifulSoup, Scrapy, or Selenium.
- Solid understanding of database technologies (S
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