Lead Data Scientist

As an experienced Lead Data Scientist with a minimum of 8 years of professional experience, including at least 6 years in a data science role, your expertise lies in statistical modeling, machine learning, deep learning, and GenAI. Python proficiency is a must, and you should have hands-on experience in optimizing code for performance. You excel in data preprocessing, feature engineering, data visualization, hyperparameter tuning, and have a solid understanding of database concepts, especially when working with large datasets. Experience in deploying and scaling machine learning models in a production environment, along with familiarity with machine learning operations (MLOps) and related tools, is expected. Your knowledge extends to Generative AI concepts and LLM finetuning, supported by excellent communication and collaboration skills. **Key Responsibilities:** - Guide and mentor a high-performance team on the latest technology landscape, patterns, and design standards - Provide strategic direction and technical leadership for AI initiatives, leading the design and architecture of complex AI systems - Develop and deploy machine learning/deep learning models to address key business challenges - Apply various techniques in statistical modeling, data preprocessing, feature engineering, and more - Proficient in areas such as computer vision, predictive analytics, natural language processing, time series analysis, and recommendation systems - Design and optimize data pipelines for model training and deployment, utilizing model serving frameworks and APIs for integration with other systems **Qualifications Required:** - Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area - Primary skills in Python, Data Science concepts, Pandas, NumPy, Matplotlib, Artificial Intelligence, Statistical Modeling, Machine Learning, Natural Language Processing (NLP), Deep Learning, Model Serving Frameworks, MLOps, Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems, Generative AI, and proficiency in Cloud Computing Platforms - Expertise in designing scalable and efficient model architectures - Ability to assess and forecast financial requirements of data science projects - Strong communication skills for conveying technical concepts to stakeholders By staying updated with the latest advancements in data science and machine learning, particularly in generative AI, you will evaluate their potential applications and serve as a primary point of contact for client managers.,