Marketing Data Scientist

Job Title: Data Scientist/Lead Data Scientist Locations: NP : Immediate Joiner - 15 Days Skills : Python , Data Science , ML Model building, GCP, Azure, AWS Tiger Analytics is a global leader in AI and analytics, helping Fortune 1000 companies solve their toughest challenges. We offer full-stack AI and analytics services & solutions to empower businesses to achieve real outcomes and value at scale. We are on a mission to push the boundaries of what AI and analytics can do to help enterprises navigate uncertainty and move forward decisively. Many of our team leaders rank in Top 10 and 40 Under 40 lists, exemplifying our dedication to innovation and excellence. Financial Times, Economic Times and Analytics India Magazine. As a Data Scientist/Senior/Lead Data Scientist, you will be at the forefront of solving high-impact business problems using advanced machine learning, data engineering, and analytics solutions. You will lead and contribute to projects involving the development, deployment, and monitoring of ML/AI models in GCP environment across industries. Lead and contribute to developing sophisticated machine learning models, predictive analytics, and statistical analyses to solve complex business problems.  Demonstrate proficiency in programming languages such as Python, with the ability to write clean, Use your robust problem-solving skills to develop data-driven solutions, analyse complex datasets, Take ownership of end-to-end model development—from problem definition and data exploration to model training, validation, deployment, and monitoring—delivering scalable solutions in real- Collaborate with cross-functional teams, including data engineers, software developers, and business stakeholders, to integrate machine learning solutions into business processes, with an emphasis on production-grade deployment.  Implement and scale AI/ML models on Google Cloud Platform using tools like Vertex AI Workbench, Vertex AI Pipelines (Kubeflow), and BigQuery to accelerate development and streamline production deployment.  Deploy, serve, and manage high-performance models using Vertex AI Endpoints, Cloud Run, and Cloud Composer, ensuring resilience and observability via Vertex Model Monitoring, Cloud Monitoring, and Logging. 4–10 year’s experience in data science and ML model development ● A passion for writing high-quality, modular, and scalable code (Python), with hands-on involvement across end-to-end project execution. ● Proven experience deploying machine learning models in production using Google Cloud Vertex AI (Training Jobs, Custom Training, Model Registry, Scoring Jobs, Experiment Tracking using Experience in orchestrating ML pipelines using Vertex AI Pipelines (Kubeflow) and/or Cloud Hands-on exposure to GCP services like Vertex AI SDK, Cloud Storage, Cloud Run, and CI/CD pipelines (GitHub Actions, Cloud Build) ● Experience with monitoring and maintaining ML models in production, using Vertex AI Model Monitoring and related GCP tools Experience with Generative AI tools like Vertex RAG Engine, Agent Builder, Dialogflow CX, and Google Agent Development Kit (ADK) ● Familiarity with API management (Apigee), VPC networking, load balancers, and GCP SDKs such Every individual comes with a different set of skills and qualities so even if you don’t tick all the boxes for the role today, we urge you to apply as there might be a suitable/unique role for you tomorrow. Note: The designation will be commensurate with expertise and experience. Compensation packages are among the best in the industry. Additional Benefits: Health insurance (self & family), virtual wellness platform, and knowledge communities.