Freelance Data Scientist & AI Engineer

Role Overview: You will be responsible for designing and implementing ML models to address complex business challenges. Additionally, you will clean, preprocess, and analyze large datasets to derive meaningful insights and model features. It will be your responsibility to train and fine-tune ML models using various techniques, evaluate model performance, optimize for efficiency and scalability, deploy ML models in production, and collaborate with data scientists, engineers, and stakeholders to integrate ML solutions. You will also stay updated on ML/AI advancements, contribute to internal knowledge, and maintain comprehensive documentation for all ML models and processes. Key Responsibilities: - Design and implement ML models to tackle complex business challenges. - Clean, preprocess, and analyze large datasets for meaningful insights and model features. - Train and fine-tune ML models using various techniques including deep learning and ensemble methods. - Assess model performance, optimize for accuracy, efficiency, and scalability. - Deploy ML models in production, monitor performance for reliability. - Work with data scientists, engineers, and stakeholders to integrate ML solutions. - Stay updated on ML/AI advancements, contribute to internal knowledge. - Maintain comprehensive documentation for all ML models and processes. Qualifications Required: - Bachelor's or master's degree in computer science, Machine Learning, Data Science, or a related field. - Minimum of 6-10 years of experience. Desirable Skills: Must Have: - Experience in timeseries forecasting, regression Model, Classification Model. - Proficiency in Python, R, and Data analysis. - Experience in handling large datasets using Panda, Numpy, and Matplotlib. - Version Control experience with Git or any other tool. - Hands-on experience with ML Frameworks such as Tensorflow, Pytorch, Scikit-Learn, and Keras. - Good knowledge of Cloud platforms (AWS/Azure/GCP) and Docker Kubernetes. - Expertise in Model Selection, evaluation, Deployment, Data collection, and preprocessing, Feature engineering. Good to Have: - Experience with Big Data and analytics using technologies like Hadoop, Spark, etc. - Additional experience or knowledge in AI/ML technologies beyond the mentioned frameworks. - Experience in BFSI and banking domain. (Note: No additional details of the company were provided in the job description),