Data Scientist- AI/ML

Role Overview: You are required for the position of a Data Scientist Engineer with a strong background in AI/ML, data collection preprocessing, estimation, and architecture creation. The role demands 6 to 10 years of experience and is based in Noida, with flexibility for travel. It is mandatory to be present in the office twice a week. This is a 6-month contract position with the possibility of extension. If interested, please share your resume at heena@aliqan.com. Key Responsibilities: - Model Development: Design and implement ML models to address complex business challenges. - Data Preprocessing: Clean, preprocess, and analyze large datasets to derive meaningful insights and model features. - Model Training: Train and fine-tune ML models using techniques such as deep learning and ensemble methods. - Evaluation and Optimization: Assess model performance, optimize for accuracy, efficiency, and scalability. - Deployment: Deploy ML models in production and monitor performance for reliability. - Collaboration: Collaborate with data scientists, engineers, and stakeholders to integrate ML solutions. - Research: Stay updated on ML/AI advancements and contribute to internal knowledge. - Documentation: Maintain comprehensive documentation for all ML models and processes. Qualification Required: - Bachelor's or master's degree in computer science, Machine Learning, Data Science, or a related field. - Experience of 6-10 years in the field. Desirable Skills: Must Have: - Experience in timeseries forecasting, regression Model, and Classification Model. - Proficiency in Python, R, and data analysis. - Handling large datasets with Panda, Numpy, and Matplot Lib. - Version Control: Git or any other. - Hands-on experience in ML Frameworks such as Tensorflow, Pytorch, Scikit-Learn, and Keras. - Good knowledge of Cloud platforms (AWS/Azure/GCP) and tools like Docker and Kubernetes. - Skills in Model Selection, evaluation, Deployment, Data collection and preprocessing, and 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. - Exposure to BFSI and banking domain.,