Data Scientist

Role Overview: As a Data Science and Machine Learning expert with over 9 years of experience, including 2+ years in leadership roles, you will be responsible for delivering and deploying ML solutions at scale within fast-paced, business-driven environments. Your expertise with modern ML frameworks such as PyTorch, TensorFlow/Keras, and Scikit-learn will be crucial in driving clear and measurable business impact. Key Responsibilities: - Lead teams or manage high-performing DS/ML groups. - Apply regression, classification, tree-based models, gradient boosting methods, time-series forecasting, NLP, optimization, and decision science techniques. - Utilize Python, SQL, Pandas, NumPy, Matplotlib, and Plotly for data manipulation, analysis, and visualization. - Build end-to-end ML workflows including feature engineering pipelines, model evaluation, A/B testing, and deployment infrastructure. - Implement MLOps practices like containerization, RESTful service development, CI/CD pipelines, version control, and scalable inference systems. - Demonstrate leadership by balancing speed vs. rigor, prioritizing effectively, and influencing senior cross-functional leaders. Qualifications Required: - 9+ years of experience in Data Science and Machine Learning. - Demonstrated success in delivering and deploying ML solutions at scale. - Strong foundation in applied machine learning, statistical modeling, and optimization. - Proficiency in Python, SQL, and ML frameworks like PyTorch, TensorFlow/Keras, and Scikit-learn. - Experience in production-grade ML systems, MLOps practices, and leadership skills. - Good-to-have: Experience in Time-Series Forecasting, MMM, Causal Inference, personalization, recommendation systems, pricing, logistics, or operational optimization. Background in high-scale industries is a plus. (Note: Any additional details of the company were not provided in the JD) Role Overview: As a Data Science and Machine Learning expert with over 9 years of experience, including 2+ years in leadership roles, you will be responsible for delivering and deploying ML solutions at scale within fast-paced, business-driven environments. Your expertise with modern ML frameworks such as PyTorch, TensorFlow/Keras, and Scikit-learn will be crucial in driving clear and measurable business impact. Key Responsibilities: - Lead teams or manage high-performing DS/ML groups. - Apply regression, classification, tree-based models, gradient boosting methods, time-series forecasting, NLP, optimization, and decision science techniques. - Utilize Python, SQL, Pandas, NumPy, Matplotlib, and Plotly for data manipulation, analysis, and visualization. - Build end-to-end ML workflows including feature engineering pipelines, model evaluation, A/B testing, and deployment infrastructure. - Implement MLOps practices like containerization, RESTful service development, CI/CD pipelines, version control, and scalable inference systems. - Demonstrate leadership by balancing speed vs. rigor, prioritizing effectively, and influencing senior cross-functional leaders. Qualifications Required: - 9+ years of experience in Data Science and Machine Learning. - Demonstrated success in delivering and deploying ML solutions at scale. - Strong foundation in applied machine learning, statistical modeling, and optimization. - Proficiency in Python, SQL, and ML frameworks like PyTorch, TensorFlow/Keras, and Scikit-learn. - Experience in production-grade ML systems, MLOps practices, and leadership skills. - Good-to-have: Experience in Time-Series Forecasting, MMM, Causal Inference, personalization, recommendation systems, pricing, logistics, or operational optimization. Background in high-scale industries is a plus. (Note: Any additional details of the company were not provided in the JD)