Senior Applied Machine Learning Engineer

📋 Description

• Production Model Optimization: Improve existing machine learning models for churn prediction
• Prediction Quality and Evaluation: Measure model performance against actual renewal, churn
• Statistical Analysis and Backtesting: Develop time-based backtesting methodologies and fixed test
• Prediction Error Investigation: Analyze incorrect predictions at the individual customer account
• Data Quality and Feature Engineering: Investigate inconsistent CRM records and product usage data
• Production Implementation: Translate analytical findings and model improvements into

🎯 Requirements

• Professional Experience: At least five years of applied machine learning experience, specifically
• Academic Foundation: Strong mathematical and statistical fundamentals, ideally supported by a
• Production ML Ownership: Demonstrated experience developing, deploying, and maintaining production
• Machine Learning Fundamentals: Strong understanding of classification methods, precision, recall
• Data Quality and Leakage Prevention: Proven ability to identify and resolve data leakage, incorrect
• Business Data Experience: Practical experience working with complex, imperfect datasets from CRM

🎁 Benefits

• Remote Work: Full-time remote opportunity for candidates based in India.
• Competitive Engagement Structure: Full-time contractor arrangement with a US-based organization
• High-Impact Responsibilities: Direct ownership of machine learning prediction quality and the
• Production-Focused Machine Learning: Work on live models and real business outcomes rather than
• Advanced Analytical Challenges: Solve practical problems involving statistical evaluation, data
• AI and Product Innovation: Contribute to new predictive capabilities for customer expansion