Advanced Data Scientist

1 week ago

Dindigul, Tamil Nadu, India beBeeMachine Full time ₹ 1,50,00,000 - ₹ 2,00,00,000

Job Overview

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We are seeking an experienced Senior Machine Learning Engineer to join our team and contribute to the development of complex data pipelines, model integration, and scalable AI/ML solutions.

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  • Main Responsibilities:">
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  • Develop and optimize complex data pipelines using machine learning engineering principles to enhance efficiency and scalability.">
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  • Integrate and optimize data and model pipelines within production environments, diagnosing data inconsistencies and documenting assumptions.">
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  • Employ experimental methodologies, statistics, and machine learning concepts to create self-running AI systems for predictive modeling.">
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  • Collaborate with data science teams to review model-ready datasets and feature documentation, ensuring completeness and accuracy.">
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  • Perform data discovery and analysis of raw data sources, applying business context to meet model development needs.">
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  • Comfort with exploratory data exploration and tracking data lineage during inception or root cause analysis.">
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  • Engage with internal stakeholders to understand business processes and translate requirements into analytical approaches.">
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  • Write and maintain model monitoring scripts, diagnosing issues and coordinating resolutions based on alerts.">
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  • Serve as a domain expert in machine learning engineering on cross-functional teams for significant initiatives.">
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  • Stay updated with the latest advancements in AI/ML and apply them to real-world challenges.">
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Requirements

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  • Undergraduate degree or equivalent experience; a graduate degree is preferred.">
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  • Minimum of 8 years of relevant work experience.">
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  • At least 3 years of hands-on experience designing ETL pipelines using AWS services (e.g., Glue, SageMaker).">
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  • Proficiency in programming languages, particularly Python (including PySpark, PySQL) and familiarity with machine learning libraries and frameworks.">
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  • Strong understanding of cloud technologies, including AWS and Azure, and experience with NoSQL databases.">
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  • Familiarity with Feature Store usage, LLMs, GenAI, RAG, Prompt Engineering, and Model Evaluation.">
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  • Experience with API design and development is a plus. Docker Kubernetes">
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  • Solid understanding of software engineering principles, including design patterns, testing, security, and version control.">
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  • Knowledge of Machine Learning Development Lifecycle (MDLC) best practices and protocols.">
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  • Understanding of solution architecture for building end-to-end machine learning data pipelines.">
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Certifications:

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