Senior Data Scientist

Primary role is to analyze data and build machine learning models using GCP services like Vertex AI and BigQuery. Lead a team of Data scientists, guide and monitor for efficiency and productivity

• Key responsibilities include the end-to-end project lifecycle, from defining business problems and collecting data to deploying and monitoring models, while collaborating with data engineers and business stakeholders to drive data-driven decisions.
• Data analysis and visualization : Analyze large datasets to identify trends, patterns, and insights. Create data visualizations and reports to communicate findings to stakeholders.
• Model development : Design, develop, and implement advanced statistical and machine learning models for tasks like forecasting, classification, and optimization using GCP tools and services.
• Data pipeline and workflow management : Collaborate with data engineers to design and optimize data pipelines, and build their own data processing, transformation, and analysis pipelines.
• Model deployment and monitoring : Deploy machine learning models into production environments on GCP and continuously monitor their performance
• Extensive, hands-on experience of working on challenging AI / ML projects in an industry setting, from ideation to deployment
• Highly proficient in programming (Python, SQL) and expert user of various AI / ML frameworks (scikit-learn, TensorFlow, PyTorch etc.) - it's a 100% hands-on role
• Strong knowledge of ML foundations, Transformers, LLM architecture, prompting and fine tuning of LLMs
• 8+ years of experience in data science and machine learning algorithms, building and deploying models and associated with entire lifecycle of model analysis / building / Deployment / assessment. Must have worked on 2 / 3 production projects as a Data Scientist
• 3+ years of a Tech or DS lead role leading programs and / or technical teams
• Good hands-on experience with Vertex AI, ML models, Vector databases, RAG.
• Experience working with business and key stakeholders to understand model requirements and build accordingly
• Strong commitment to work and ownership
• Demonstrable impact of work on the business bottomline (money saved, efficiency gain, better security etc.)
• Familiarity with at least one public cloud services (GCP, AWS, Azure), preference will be given to GCP and Vertex AI
• Design, development and deployment of ML pipelines in the cloud
• Experience with MLOps and operationalizing models in production, lifecycle management of models
• Data governance : Adhere to data security and compliance standards.

Behavioral skills :