Roles and Responsibilities

• Develop, implement, and optimize machine learning models, predictive algorithms, and AI solutions.
• Perform data cleaning, preprocessing, feature engineering, and exploratory data analysis to extract insights from structured and unstructured data.
• Design and maintain end-to-end ML pipelines, from model development to deployment and monitoring.
• Collaborate with engineering teams to integrate ML models into production systems.
• Conduct statistical analysis to validate model performance and ensure accuracy and robustness.
• Utilize AI techniques such as NLP, deep learning, and reinforcement learning (as applicable).
• Communicate analytical findings to stakeholders through dashboards, reports, and presentations.
• Stay current with the latest developments in AI/ML, data science tools, and industry best practices.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or related field.
• Proven experience as a Data Scientist or Machine Learning Engineer.
• Strong skills in Python and ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Proficiency with data manipulation tools (Pandas, NumPy) and SQL/NoSQL databases.
• Experience with data visualization tools (Tableau, Power BI, Matplotlib, Seaborn).
• Familiarity with cloud platforms (AWS, Azure, GCP) and ML Ops tools is a plus.
• Solid understanding of statistics, probability, and machine learning algorithms.

Preferred Qualifications

• Experience with large language models (LLMs) or generative AI.
• Knowledge of big data technologies (Spark, Hadoop).
• Hands-on experience with API development and ML model deployment.
• Background in working with unstructured data (text, images, audio).

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