Data Scientist Engineer

Job Description Role Overview: You are required to be a data scientist engineer with strong experience in Artificial Intelligence (AI) and Machine Learning (ML), specializing in data collection preprocessing, estimation, and architecture creation. Key Responsibilities: - Design and implement ML models to address complex business challenges. - Clean, preprocess, and analyze large datasets to derive meaningful insights and create model features. - Train and fine-tune ML models using various techniques such as deep learning and ensemble methods. - Evaluate model performance, optimize for accuracy, efficiency, and scalability. - Deploy ML models in production and monitor their performance for reliability. - Collaborate with data scientists, engineers, and stakeholders to integrate ML solutions. - Stay updated on advancements in ML/AI, contributing to internal knowledge. - Maintain comprehensive documentation for all ML models and processes. Qualifications: - Bachelor's or master's degree in Computer Science, Machine Learning, Data Science, or a related field. - 6-10 years of experience. Desirable Skills: Must Have: - Experience in timeseries forecasting, regression Model, and Classification Model. - Proficiency in Python, R, and data analysis. - Handling large datasets with Pandas, NumPy, and Matplotlib. - Familiarity with version control using Git or any other tool. - Hands-on experience with ML frameworks like TensorFlow, PyTorch, Scikit-Learn, and Keras. - Knowledge of Cloud platforms such as AWS, Azure, GCP, Docker, and Kubernetes. - Expertise in model selection, evaluation, deployment, data collection, 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. - Domain knowledge in BFSI and banking. Role Overview: You are required to be a data scientist engineer with strong experience in Artificial Intelligence (AI) and Machine Learning (ML), specializing in data collection preprocessing, estimation, and architecture creation. Key Responsibilities: - Design and implement ML models to address complex business challenges. - Clean, preprocess, and analyze large datasets to derive meaningful insights and create model features. - Train and fine-tune ML models using various techniques such as deep learning and ensemble methods. - Evaluate model performance, optimize for accuracy, efficiency, and scalability. - Deploy ML models in production and monitor their performance for reliability. - Collaborate with data scientists, engineers, and stakeholders to integrate ML solutions. - Stay updated on advancements in ML/AI, contributing to internal knowledge. - Maintain comprehensive documentation for all ML models and processes. Qualifications: - Bachelor's or master's degree in Computer Science, Machine Learning, Data Science, or a related field. - 6-10 years of experience. Desirable Skills: Must Have: - Experience in timeseries forecasting, regression Model, and Classification Model. - Proficiency in Python, R, and data analysis. - Handling large datasets with Pandas, NumPy, and Matplotlib. - Familiarity with version control using Git or any other tool. - Hands-on experience with ML frameworks like TensorFlow, PyTorch, Scikit-Learn, and Keras. - Knowledge of Cloud platforms such as AWS, Azure, GCP, Docker, and Kubernetes. - Expertise in model selection, evaluation, deployment, data collection, 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. - Domain knowledge in BFSI and banking.