Senior Data Science Professional

3 days ago

rajahmundry, India beBeeDataScientist Full time

Job Title: Data Science LeaderLocation: Remote / Hybrid (Adjust as needed) Department: Data & AI Employment Type: Full-timeAbout the RoleAs a Senior Data Scientist, you will lead end-to-end development of data science and ML solutions from problem framing to model deployment in production.You will partner closely with product, engineering, and business stakeholders to deliver measurable impact using machine learning, experimentation, and advanced analytics on top of AWS data and ML services.Key Responsibilities1. Problem Definition & Stakeholder CollaborationWork with business, product, and engineering teams to translate ambiguous problems into clear data science use cases and success metrics.Define hypotheses, experimentation strategies, and measurable outcomes for ML and analytics initiatives.2. Data & Feature Engineering (AWS-native)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.3. Modeling & AnalyticsBuild, train, and optimize models for use cases such as 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.4. MLOps & Deployment (AWS SageMaker)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.5. Leadership & MentoringProvide 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.Required Skills and QualificationsThe ideal candidate has 7+ years of experience in data science or applied machine learning roles. Strong proficiency in Python and ML/data libraries is required, along with demonstrated experience building and deploying ML solutions on AWS.Detailed understanding of statistics, experimental design, and causal inference, including A/B testing, hypothesis testing, confidence intervals, etc., is also necessary.Strong SQL skills and comfort working with large-scale datasets in data lake / data warehouse environments are essential.Excellent communication skills – able to explain complex topics to both technical and non-technical stakeholders – are also required.Preferred qualifications include experience with streaming data / real-time ML, feature stores, and ML observability tools.AWS certifications such as AWS Certified Machine Learning – Specialty or AWS Data Analytics – Specialty are highly valued.],

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