Data Model Architect

4 days ago

Coimbatore, Tamil Nadu, India beBeeMachineLearning Full time ₹ 1,50,00,000 - ₹ 2,50,00,000
Business Analyst for Advanced Data Models

This is a highly specialized position that involves leveraging strong ML model experience to drive business objectives and improve efficiency.

Key Responsibilities:

  • Leverage expertise in machine learning to architect, design, and develop robust solutions with a focus on integrating Large Language Models (LLMs) where applicable.
  • Collaborate effectively within Agile Scrum teams, contributing to iterative development and continuous improvement.
  • Document business processes, workflows, and requirements clearly and comprehensively.
  • Engage in close collaboration with various domains within the organization to ensure alignment and understanding of business needs.
  • Participate in collaborative conceptualization sessions to brainstorm and refine project ideas.

Technical Skills and Qualifications:

  • Proficiency in Python, Machine Learning, REST API, and SQL.
  • Experience with data processing, cleansing, and verification to ensure data integrity for analysis.
  • Conduct data quality checks and exploratory analyses to inform model development.
  • Demonstrated programming skills in relevant languages, particularly Python and API development.
  • Build end-to-end machine learning models, including data structures and transformation processes.
  • Strong understanding of statistical modeling techniques (e.g., Regression, Clustering, Decision Trees, Logistic Regression).
  • Familiarity with machine learning algorithms (e.g., KNN, Random Forests, Ensemble Methods, Bayesian/Markov Networks).
  • Knowledge of data mining concepts and experience with data visualization tools and dashboards.

Professional Growth and Benefits:

  • Stay updated with the latest advancements in machine learning and natural language processing, particularly in the context of LLMs.
  • Mentor junior team members on best practices in machine learning and LLM implementation.
  • Contribute to the development of best practices and standards for machine learning and LLM projects within the organization.

Why is this role important?

This role is crucial as it involves leveraging strong ML model experience to drive business objectives and improve efficiency. The ability to integrate Large Language Models (LLMs) into existing systems is also vital.

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