Chief Data Architect

2 days ago

Salem, Tamil Nadu, India beBeeDataScientist Full time ₹ 1,50,00,000 - ₹ 2,50,00,000

Job Overview:

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The ideal candidate will possess a strong background in machine learning, with experience in building, deploying, and evaluating ML/NLP/GenAI systems. They should have a solid understanding of system design principles and be proficient in programming languages such as Python.

Key Responsibilities:

  • ">
  • Developing Data-Driven Solutions: Design, plan, prototype, productionize, maintain, and document reliable and scalable data science products in complex environments.">
  • Collaboration and Communication: Work closely with other data scientists, data engineers, software engineers, data managers, and business partners to deliver impactful data science products.">
  • Business Insights: Conduct data analyses to yield actionable business insights that drive strategic decision-making.">
  • Tool Proficiency: Demonstrate expertise in a range of data science tools and approaches across all data lifecycle stages.">

Requirements:

  • ">
  • Programming Skills: Strong Python and intermediate SQL skills.">
  • Machine Learning Experience: Experience building, deploying, and evaluating ML/NLP/GenAI systems.">
  • System Design: Experience with ML system design.">
  • Communication: Very strong (including written) communication skills and ability to break down and articulate complex tasks into implementation strategies.">
  • Software Engineering: Software engineering best practices, including testing, OOP, etc.">
  • Cloud Systems: Knowledge of cloud systems, especially Azure preferred.">
  • Mathematical Optimizers: A more traditional ML perspective, some knowledge and understanding of mathematical optimizers, how to select the best ones for purpose and set parameters.">
  • Hands-on Experience: Hands-on experience (typically 5+ years) designing, planning, prototyping, productionizing, maintaining and documenting reliable and scalable data science products in complex environments.">
  • Data Science Tools: Applied knowledge of data science tools and approaches across all data lifecycle stages.">
  • Mathematical Foundations: Thorough understanding of underlying mathematical foundations of statistics and machine learning.">
  • Programming Languages: Development experience in one or more object-oriented programming languages (e.g. Python, Go, Java, C++).">
  • Advanced SQL: Advanced SQL knowledge.">
  • Experimental Design: Knowledge of experimental design and analysis.">
  • Customer-Centric: Customer-centric and pragmatic mindset. Focus on value delivery and swift execution, while maintaining attention to detail.">
"],

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