Data Scientist Artificial Intelligence/Machine Learning

Job description

<p><p><b>Description :</b><br/><br/><b>Job Title :</b> Data Scientist<br/><br/><b>Experience :</b> 5+ Years<br/><br/><b>Location :</b> Remote/ Indore/ Mumbai/ Chennai/ Gurugram<br/><br/><b>Industry :</b> Must be from BPO/KPO or Healthcare Org or Shared Services<br/><br/><b>Key Responsibilities :</b><br/><br/>AI/ML Development & Research :<br/><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/>Cloud Infrastructure & Full-Stack Development :<br/><br/></p><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<br/><br/>Data Engineering & Database Management :<br/><br/></p><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/>Leadership & Collaboration :<br/><br/></p><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><br/>- 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 Core AI/ML :</b></p><p><br/>- 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 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><br/>- 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><br/>- 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.)<br/><br/></p><p>- Machine Learning : Scikit-learn<br/><br/></p><p>- Deep Learning : TensorFlow<br/><br/></p><p>- Programming : Python (expert), R, Java/Scala, JavaScript/TypeScript<br/><br/></p><p>- Cloud Platforms : AWS (SageMaker, EC2, S3, Lambda)<br/><br/></p><p>- vector databases and embeddings (Pinecone, Weaviate, Chroma)<br/><br/></p><p>- Knowledge of LangChain, LlamaIndex, or similar LLM frameworks</p><br/></p> (ref:hirist.tech)

Required Skill Profession

Mathematical Science Occupations