Chief Data Innovation Officer

7 days ago

coimbatore, India beBeeDataScience Full time

Lead Data Science InnovatorOur organization is seeking an experienced Senior Data Scientist to lead the development of data science and machine learning solutions. The successful candidate will be responsible for designing and building robust data pipelines, developing scalable feature stores, and ensuring data quality and governance.About the RoleDefine hypotheses, experimentation strategies, and measurable outcomes for ML and analytics initiatives.Work with business, product, and engineering teams to translate ambiguous problems into clear data science use cases and success metrics.ResponsibilitiesProblem Definition & Stakeholder CollaborationTranslate complex problems into actionable data science opportunities.Collaborate with stakeholders to identify key performance indicators and success metrics.Data & Feature Engineering (AWS-native)Design and build efficient data pipelines using AWS services.Develop reusable data assets and scalable feature stores for multiple ML use cases.Ensure data quality and observability in collaboration with data engineering teams.Modeling & AnalyticsBuild, train, and optimize models for prediction, recommendation, forecasting, and other use cases.Use Python and standard ML libraries for experimentation and prototyping.Design and run A/B tests, holdout experiments, and causal analyses to measure impact.MLOps & Deployment (AWS SageMaker)Productionize models using Amazon SageMaker.Implement CI/CD for ML and monitoring for model drift, data drift, and performance degradation.Optimize cost and performance of deployed models and pipelines.Leadership & MentoringProvide technical leadership on projects and set standards for experimentation, documentation, and code quality.Mentor junior data scientists and analysts and contribute to best practices and internal tooling.Requirements7+ years of experience in data science or applied machine learning roles.Strong proficiency in Python and ML/data libraries.Demonstrated experience building and deploying ML solutions on AWS, including data, ML, orchestration/integration, and solid understanding of statistics and experimental design.Proven track record of delivering ML solutions into production with measurable business impact.Strong SQL skills and comfort working with large-scale datasets in data lake/data warehouse environments.Excellent communication skills to explain complex topics to both technical and non-technical stakeholders.Preferred QualificationsExperience with streaming data/real-time ML using Kinesis, Kafka/MSK, or similar.Experience with feature stores and ML observability tools.Domain experience in marketing analytics, customer personalization, fraud/risk, pricing, demand forecasting, or operations optimization.Familiarity with MLOps best practices.AWS certifications such as AWS Certified Machine Learning – Specialty or AWS Data Analytics – Specialty.

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