ML Lead

As a highly experienced Machine Learning Lead, your role will involve driving the architecture, development, and deployment of advanced machine learning solutions. You will lead a talented technical team and act as the critical bridge between engineering efforts and clients. Your ability to simplify complex ML concepts into clear, business-driven language for stakeholders will ensure successful project delivery. Key Responsibilities: - Stakeholder Communication & Client Management: Serve as the primary technical liaison for clients, translating complex ML terms into actionable business insights for non-technical stakeholders. - Technical Leadership: Architect and design end-to-end ML solutions, while mentoring and guiding a team of Data Analysts and ML/Data Engineers. - Project Delivery: Oversee the collection, cleanup, exploration, and analysis of complex datasets to drive business intelligence. - Model Lifecycle Management: Lead the implementation, deployment, and scaling of advanced ML models and algorithms to solve complex business problems. - Cross-functional Collaboration: Collaborate with data engineers to design and monitor robust data and MLOps pipelines for ongoing business operations. - Strategic Alignment: Understand the client's core business model to ensure measurable ROI from ML solutions. Qualifications Required: - Experience: 8 to 12 years of overall industry experience in Data Science, Machine Learning, and technical leadership. - Client-Facing Expertise: Demonstrated experience in stakeholder management and confidently explaining complex ML concepts. - Technical Proficiency: Hands-on coding experience in Python and familiarity with popular ML frameworks like Scikit-Learn, TensorFlow, and PyTorch. - Analytical Rigor: Expertise in statistical modeling of large datasets and a comprehensive understanding of diverse ML algorithms. - Pipeline & Architecture: Strong experience in designing robust data/ML pipelines and transitioning models to production environments. - Data Analytics: Foundational experience in data analytics, with the ability to derive actionable insights from raw data. Additional Company Details: The company offers a competitive salary, a hybrid work model, rapid learning opportunities, and reimbursement for basic home office setups. Location: Chennai / Mumbai / Pune / Hyderabad / Bangalore (Hybrid) As a highly experienced Machine Learning Lead, your role will involve driving the architecture, development, and deployment of advanced machine learning solutions. You will lead a talented technical team and act as the critical bridge between engineering efforts and clients. Your ability to simplify complex ML concepts into clear, business-driven language for stakeholders will ensure successful project delivery. Key Responsibilities: - Stakeholder Communication & Client Management: Serve as the primary technical liaison for clients, translating complex ML terms into actionable business insights for non-technical stakeholders. - Technical Leadership: Architect and design end-to-end ML solutions, while mentoring and guiding a team of Data Analysts and ML/Data Engineers. - Project Delivery: Oversee the collection, cleanup, exploration, and analysis of complex datasets to drive business intelligence. - Model Lifecycle Management: Lead the implementation, deployment, and scaling of advanced ML models and algorithms to solve complex business problems. - Cross-functional Collaboration: Collaborate with data engineers to design and monitor robust data and MLOps pipelines for ongoing business operations. - Strategic Alignment: Understand the client's core business model to ensure measurable ROI from ML solutions. Qualifications Required: - Experience: 8 to 12 years of overall industry experience in Data Science, Machine Learning, and technical leadership. - Client-Facing Expertise: Demonstrated experience in stakeholder management and confidently explaining complex ML concepts. - Technical Proficiency: Hands-on coding experience in Python and familiarity with popular ML frameworks like Scikit-Learn, TensorFlow, and PyTorch. - Analytical Rigor: Expertise in statistical modeling of large datasets and a comprehensive understanding of diverse ML algorithms. - Pipeline & Architecture: Strong experience in designing robust data/ML pipelines and transitioning models to production environments. - Data Analytics: Foundational experience in data analytics, with the ability to derive actionable insights from raw data. Additional Company Details: The company offers a competitive salary, a hybrid work model, rapid learning opportunities, and reimbursement for basic home office setups. Location: Chennai / Mumbai / Pune / Hyderabad / Bangalore (Hybrid)