InfoCepts - Data Science Consultant - Machine Learning

Job Summary:We are looking for an experienced Data Science Consultant to lead the design, development, and deployment of advanced data science and AI solutions that drive business transformation and operational excellence. The ideal candidate will have strong expertise in Machine Learning, Deep Learning, Forecasting, Python, PySpark, and Cloud Technologies, with experience building scalable, production-ready AI models. This role requires close collaboration with business stakeholders to deliver innovative, data-driven solutions across multiple business domains.Key Responsibilities:- Design, develop, and deploy end-to-end data science and machine learning solutions to solve complex business problems.- Build predictive models for forecasting, anomaly detection, and operational optimization using advanced machine learning and deep learning techniques.- Develop scalable data processing and feature engineering pipelines using Python, PySpark, and distributed computing frameworks.- Design, train, evaluate, and deploy deep learning models using TensorFlow and PyTorch.- Implement Convolutional Neural Networks (CNNs) and other advanced machine learning algorithms for forecasting and pattern recognition.- Deploy and monitor AI/ML models in production environments, ensuring scalability, reliability, and performance.- Collaborate with cross-functional teams to identify business opportunities and translate them into AI-driven solutions.- Ensure adherence to AI governance, model monitoring, and Responsible AI best practices.- Build and optimize data pipelines using Spark, Databricks, and cloud-native services.- Document technical solutions, model methodologies, and deployment processes.- Stay updated with emerging AI, GenAI, and MLOps technologies and recommend innovative solutions.Required Skills:- 6+ years of experience in Data Science, Machine Learning, or Artificial Intelligence.- Strong programming skills in Python and PySpark.- Hands-on experience with TensorFlow and PyTorch.- Strong knowledge of Deep Learning, CNNs, forecasting models, and anomaly detection techniques.- Experience developing and deploying machine learning models in production environments.- Expertise with distributed computing platforms such as Apache Spark and Databricks.- Strong understanding of data preprocessing, feature engineering, and model evaluation.- Knowledge of AI Governance, Responsible AI, and model lifecycle management.- Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).- Experience with Docker, Kubernetes, and containerized AI deployments.- Strong analytical, problem-solving, and communication skills. (ref:hirist.tech)