We are seeking a highly skilled and passionate Data Scientist to design, build, and productionize enterprise-grade analytics and GenAI-powered solutions that enhance insights, recommendations, and decision-making across enterprise platforms.
The role focuses on developing, deploying, and operating machine learning and applied GenAI models?including LLM-based insight generation, summarization, and decision augmentation?using large-scale structured and semi-structured data, with strong emphasis on scalability, reliability, governance, and enterprise readiness.
Skills:
� Strong foundation in statistics, machine learning, and applied data science, including feature engineering, model evaluation, and performance tuning.
� Experience building predictive, descriptive, and prescriptive models on large-scale structured and semi-structured data.
� Proficiency in Python, SQL, and Spark, with hands-on experience in data processing and analytical pipelines.
� Hands-on experience with the Databricks ecosystem (Databricks SQL, MLflow, Feature Store, and Jobs) to build, deploy, and monitor data science and GenAI solutions at enterprise scale.
� Experience with ML frameworks such as PyTorch and/or TensorFlow for model development and experimentation.
� Hands-on experience using LangChain and LangGraph to operationalize LLM-based analytical workflows, including RAG and prompt design, and evaluation techniques, with focus on analytical and decision-support use cases.
� Practical exposure to MLOps / LLMOps practices, including model and prompt versioning, deployment, monitoring, and retraining.
� Experience tracking model quality, drift, and GenAI output reliability in production.
� Strong understanding of data quality, explainability, responsible AI, and enterprise governance requirements.
Qualifications and Experience:
8+ years of experience in Data Science / AI Engineering, including:
� 6+ years building and deploying machine learning models (supervised, unsupervised, and time-series), covering feature engineering, model evaluation, and performance optimization.
� 4+ years working with NLP or language-based systems, including text classification, information extraction, and semantic modeling.
� 2+ years delivering GenAI or conversational AI solutions in production, with focus on applied LLM use cases, RAG, and enterprise deployment.