Data Science Innovator

1 week ago

kozhikode, India beBeeData Full time

We're seeking an accomplished Senior Data Science Leader to spearhead the development of end-to-end data science and machine learning solutions.This is a highly collaborative role, requiring close partnerships with product, engineering, and business stakeholders to drive measurable impact through experimentation, analytics, and AI.Problem Definition & Stakeholder Collaboration: Work with cross-functional teams to frame ambiguous problems into clear use cases and success metrics. Define hypotheses, experimentation strategies, and outcomes for ML and analytics initiatives.Data & Feature Engineering: Design and build robust data pipelines using AWS services such as S3, Glue, Athena, Redshift, EMR, Lambda, Step Functions. Develop scalable feature stores and reusable data assets for multiple ML use cases. Ensure data quality, observability, and governance in collaboration with data engineering teams.Modeling & Analytics: Build, train, and optimize models for prediction, recommendation, forecasting, personalization, segmentation, anomaly detection, etc. Use Python and standard ML libraries (e.g., scikit-learn, XGBoost, PyTorch/TensorFlow) for experimentation and prototyping. Design and run A/B tests, holdout experiments, and causal analyses to measure impact.MLOps & Deployment: Productionize models using Amazon SageMaker (training, tuning, endpoints, pipelines, model registry). Implement CI/CD for ML, monitoring and alerting for model drift, data drift, and performance degradation. Optimize cost and performance of deployed models and pipelines.Leadership & Mentoring: Provide technical leadership on projects, setting standards for experimentation, documentation, and code quality. Mentor junior data scientists and analysts; contribute to best practices, templates, and internal tooling. Advocate for data-driven decision-making across the organization.Requirements:7+ years of hands-on experience in data science or applied machine learning roles.Strong proficiency in Python and ML/data libraries (pandas, numpy, scikit-learn, XGBoost, PyTorch/TensorFlow).Demonstrated experience building and deploying ML solutions on AWS, including:Data: S3, Glue, Athena, Redshift, EMR / AWS Lake FormationML: SageMaker (training jobs, endpoints, pipelines, model registry)Orchestration/Integration: Lambda, Step Functions, EventBridge, API GatewaySolid understanding of statistics, experimental design, and causal inference (A/B testing, hypothesis testing, confidence intervals, etc.).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—able to explain complex topics to both technical and non-technical stakeholders.Awarded candidates will possess strong teamwork and interpersonal skills, with the ability to articulate complex ideas to diverse audiences.

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