Senior Data Scientist / Machine Learning Engineer
Omnissa
Bengaluru, Karnataka, IndiaSENIOR
Job Description
Omnissa is looking for a Lead Data Scientist to advance AI/ML and analytics capabilities.
Responsibilities
- Design and develop advanced machine learning models using structured, semi-structured, and unstructured data
- Build and scale end-to-end ML pipelines, including data ingestion, feature engineering, model training, validation, deployment, and monitoring
- Lead the development of AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI agents
- Collaborate with engineering teams to deploy and operationalize models and AI systems in production environments
- Optimize models and pipelines for performance, scalability, reliability, and cost efficiency
- Perform deep-dive analyses to uncover actionable insights, trends, and opportunities
- Translate analytical findings into clear recommendations that influence product strategy and go-to-market decisions
- Drive adoption of best practices in machine learning engineering, experimentation, and model lifecycle management
- 7 to 13 years of experience in Data Science, Machine Learning, or related roles
- Strong analytical thinking and problem-solving skills, with attention to detail
- Hands-on experience in one or more of the following areas (experience across multiple domains preferred):
- Supervised and unsupervised learning
- Classification and regression
- Clustering and segmentation
- Time-series analysis
- Anomaly detection
- Recommendation Systems
- Natural Language Processing (NLP) / Information Retrieval
- Strong programming expertise in Python and SQL
Qualifications
- Hands-on experience deploying, productionizing, and monitoring ML models and AI agentic systems on AWS; familiarity with Azure or GCP is a plus
- Ability to translate business problems into AI/ML solutions, define success metrics and measure business impact of deployed solutions
- Excellent communication skills, with the ability to present complex analyses to both technical and non-technical audiences
- Bachelor’s or Master’s degree in Computer Science, Data Science, or related field
- Understanding of SaaS business metrics such as ARR, NRR, GRR, churn, retention, and ACV
- Familiarity with Salesforce or go-to-market (GTM) analytics systems
- Knowledge of data governance, schema design, and scalable data infrastructure
- Ability to thrive in a fast-paced environment and manage multiple priorities independently