Data Scientist

Job Description

Job Description

Job Title : Data Scientist – Machine Learning, Big Data, GenAI (8–10 Years Experience)

Location : Remote

Employment Type : Contract

About the Role

We are seeking a highly experienced Data Scientist with 8–10 years of expertise delivering production-grade AI / ML solutions at scale. This role requires deep technical proficiency in Machine Learning, Big Data, Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) , combined with hands-on cloud experience (AWS, Azure, or GCP) and migration expertise for modernizing data and AI platforms.

The ideal candidate can lead projects end-to-end, from architecture design to deployment, while mentoring teams, optimizing for performance and cost, and ensuring alignment with business objectives.

Key Responsibilities

• Design, develop, and deliver end-to-end ML / AI solutions in cloud-native environments from design to deployment and monitoring.
• Architect and implement Generative AI solutions leveraging LLMs (e.g., GPT, LLaMA, Claude, Mistral) and RAG pipelines with vector search.
• Build and optimize Big Data pipelines using Apache Spark, PySpark, and Delta Lake integrated with cloud storage (AWS S3, Azure Data Lake, GCP Cloud Storage).
• Design and maintain data lakehouse architectures with Databricks, Snowflake, or Delta Lake .
• Deploy scalable MLOps pipelines using MLflow, SageMaker, Azure ML, or Vertex AI with Docker, Kubernetes (EKS, AKS, GKE) , and CI / CD.
• Implement and manage vector databases (Pinecone, FAISS, Milvus, Weaviate, ChromaDB) for RAG applications.
• Oversee ETL / ELT workflows and pipeline orchestration using Airflow, dbt, or Azure Data Factory .
• Migration projects , on-prem to cloud, cross-cloud, or legacy platform upgrades (e.g., Hadoop to Databricks, Hive to Delta Lake) , ensuring data integrity and minimal downtime.
• Integrate streaming data solutions using Apache Kafka and real-time analytics frameworks.
• Conduct feature engineering, hyperparameter tuning, and model optimization for performance and scalability.
• Mentor junior data scientists and guide best practices for AI / ML development and deployment.
• Collaborate with product, engineering, and executive teams to align AI solutions with business KPIs and compliance requirements .

Required Skills & Experience

Preferred Qualifications