Data Scientist Artificial Intelligence/Machine Learning

Job description

<p><p><b>Position : </b>Data Scientist.<br/><br/> <b>Experience :</b> Min 3 Years.<br/><br/> <b>Work Mode :</b> Remote.<br/><br/> <b>Notice Period :</b> Max.30 Days (45 for Notice Serving).<br/><br/> <b>Interview Process :</b> 2 Rounds.<br/><br/> <b>Interview Mode :</b> Virtual Face-to-Face.<br/><br/> <b>Interview Timeline :</b> 1 Week.<br/><br/> <b>Industry :</b> Must be from a BPO/ KPO/ Shared Services or Healthcare Org.<br/><br/> <b>Key Responsibilities :</b></p><p><br/></p><p><b>AI/ML Development & Research :</b></p><p><br/></p><p>- Design, develop, and deploy advanced machine learning and deep learning models to solve complex business problems.<br/><br/></p><p> - Implement and optimize Large Language Models (LLMs) and Generative AI solutions for real-world applications.<br/><br/></p><p> - Build agent-based AI systems with autonomous decision-making capabilities.<br/><br/></p><p> - Conduct cutting-edge research on emerging AI technologies and explore their practical applications.<br/><br/></p><p> - Perform model evaluation, validation, and continuous optimization to ensure high performance.<br/><br/> <b>Cloud Infrastructure & Full-Stack Development :</b></p><p><p><b><br/></b></p> - Architect and implement scalable, cloud-native ML/AI solutions using AWS, Azure, or GCP.<br/><br/></p><p> - Develop full-stack applications that seamlessly integrate AI models with modern web technologies.<br/><br/></p><p> - Build and maintain robust ML pipelines using cloud services (e.g., SageMaker, ML Engine).<br/><br/></p><p> - Implement CI/CD pipelines to streamline ML model deployment and monitoring processes.<br/><br/></p><p>- Design and optimize cloud infrastructure to support high-performance computing workloads.</p><p><br/> <b>Data Engineering & Database Management :</b></p><p><p><b><br/></b></p> - Design and implement data pipelines to enable large-scale data processing and real-time analytics.<br/><br/></p><p> - Work with both SQL and NoSQL databases (e.g., PostgreSQL, MongoDB, Cassandra) to manage structured and unstructured data.<br/><br/></p><p> - Optimize database performance to support machine learning workloads and real-time applications.<br/><br/></p><p> - Implement robust data governance frameworks and ensure data quality assurance practices.<br/><br/></p><p> - Manage and process streaming data to enable real-time decision-making.<br/><br/> <b>Leadership & Collaboration :</b></p><p><p><b><br/></b></p> - Mentor junior data scientists and assist in technical decision-making to drive innovation.<br/><br/></p><p> - Collaborate with cross-functional teams, including product, engineering, and business stakeholders, to develop solutions that align with organizational goals.<br/><br/></p><p> - Present findings and insights to both technical and non-technical audiences in a clear and actionable manner.<br/><br/></p><p> - Lead proof-of-concept projects and innovation initiatives to push the boundaries of AI/ML applications.<br/><br/> <b>Required Qualifications :</b><br/><br/> <b>Education & Experience :</b></p><p><p><b><br/></b></p> - Masters or PhD in Computer Science, Data Science, Statistics, Mathematics, or a related field.<br/><br/></p><p> - 5+ years of hands-on experience in data science and machine learning, with a focus on real-world applications.<br/><br/></p><p> - 3+ years of experience working with deep learning frameworks and neural networks.<br/><br/></p><p> - 2+ years of experience with cloud platforms and full-stack development.<br/><br/> <b>Technical Skills AI/ML :</b></p><p><b><br/></b></p> - Machine Learning : Proficient in Scikit-learn, XGBoost, LightGBM, and advanced ML algorithms.<br/><br/></p><p> - Deep Learning : Expertise in TensorFlow, PyTorch, Keras, CNNs, RNNs, LSTMs, and Transformers.<br/><br/></p><p> - Large Language Models : Experience with GPT, BERT, T5, fine-tuning, and prompt engineering.<br/><br/></p><p> - Generative AI : Hands-on experience with Stable Diffusion, DALL-E, text-to-image, and text generation </p><p>models.<br/><br/></p><p> - Agentic AI : Knowledge of multi-agent systems, reinforcement learning, and autonomous agents.<br/><br/> <b>Technical Skills Development & Infrastructure :</b></p><p><p><b><br/></b></p> - Programming : Expertise in Python, with proficiency in R, Java/Scala, JavaScript/TypeScript.<br/><br/></p><p> - Cloud Platforms : Proficient with AWS (SageMaker, EC2, S3, Lambda), Azure ML, or Google Cloud AI.<br/><br/></p><p> - Databases : Proficiency with SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Cassandra, DynamoDB).<br/><br/></p><p> - Full-Stack Development : Experience with React/Vue.js, Node.js, FastAPI, Flask, Docker, Kubernetes.<br/><br/></p><p> - MLOps : Experience with MLflow, Kubeflow, model versioning, and A/B testing frameworks.<br/><br/></p><p> - Big Data : Expertise in Spark, Hadoop, Kafka, and streaming data processing.<br/><br/> <b>Non Negotiables :</b></p><p><p><b><br/></b></p> - Cloud Infrastructure ML/AI solutions on AWS, Azure, or GCP.<br/><br/></p><p> - Build and maintain ML pipelines using cloud services (SageMaker, ML Engine, etc.).<br/><br/></p><p> - Implement CI/CD pipelines for ML model deployment and monitoring.<br/><br/></p><p>- Work with both SQL and NoSQL databases (PostgreSQL, MongoDB, Cassandra, etc.).</p><p><br/></p><p> - Industry : Must be a BPO or Healthcare Org.</p><br/></p> (ref:hirist.tech)

Required Skill Profession

Mathematical Science Occupations