Data Scientist

Responsibilities

• Collaborate with Product Management and cross-functional stakeholders to define problem statements, develop solution strategies, and design scalable ML systems .
• Create insightful data visualizations , technical reports, and presentations to communicate findings to technical and non-technical audiences.
• Deploy ML models in production and implement monitoring frameworks to ensure model performance, stability, and continuous improvement.
• Design, develop, and deploy Machine Learning models.

Requirements

• The ideal candidate has a strong background in machine learning, especially in the NLP/GenAI domain.
• Requirements: BS, MS, or Ph.D. in Computer Science, Statistics , or a related field . 2-5 years of
• experience in Machine Learning projects, including model development, deployment, and optimization.
• Deep understanding of ML algorithms , their mathematical foundations , and real-world trade-offs.
• E xpertise in N LP techniques like Named Entity Recognition , I nformation Retrieval, Text classification, Text-to-Text Generation etc. Familiarity and working experience of GenAI applications ,
• Experience with prompting, fine -tuning and optimizing LLMs.
• Knowledge of recent advancements and trends in GenAI , demonstrating a commitment to continuous learning in this rapidly evolving field. Hands-on
• experience with ML frameworks such as Scikit-Learn, TensorFlow, PyTorch , LangChain , vLLM etc. Strong programming skills in Python and/or Java .
• Experience in SQL, Pandas, and PySpark for efficient data manipulation.
• Familiarity with microservice architectures , CI/CD, MLOps best practices.
• Nice to Have: Familiarity with distributed computing frameworks such as Hadoop, Spark, and OpenSearch .
• Published research in AI/ML in peer-reviewed journals or top conferences (e.g., NeurIPS , ICML, CVPR). Prior
• experience applying AI/ML to cybersecurity use cases . Basic proficiency in Unix/Linux environments for scripting and automation .

Additional details