Job Description

• Pune, Maharashtra

About Zinrelo

Zinrelo is a fast-growing SaaS product company headquartered in Silicon Valley, California with an office in Pune, India. Zinrelo offers a leading loyalty rewards platform that helps Colgate Palmolive, Jelly Belly, Western Digital, BIC and many other global brands to launch holistic loyalty programs. Zinrelo combines technology with deep data analytics and ongoing strategy consultation to unlock multiple dimensions of loyalty, including transactional, social, advocacy, engagement, behavioral, and emotional. Zinrelo’s loyalty platform is used by thousands of customers in 50+ countries. Zinrelo was founded by successful serial entrepreneurs who are graduates of IIT Kanpur with over 50 years of joint experience. Zinrelo is highly profitable and is growing quickly. 

About the Role

Data science and analytics is a strategic initiative at Zinrelo. The AI/ML engineer will lead the effort to incorporate reliable and scalable machine learning solutions and enable intelligence (AI-based features) in the Zinrelo product by harnessing the wealth of data from our loyalty platform. It is an exciting opportunity to leverage data science, machine learning, and analytics to maximize the value of data for our customers, and in turn, make it a significant market differentiator and growth engine for Zinrelo.

Responsibilities

• Collaborate with cross-functional teams to solve business problems using machine learning techniques.
• Design, develop, and implement machine learning models using tools such as Amazon SageMaker, Posit, and TensorFlow.
• Use ML models to create meaningful customer segments and recommend hyper-personalized promotions for these segments.
• Enable ML-driven actionable insights and innovations for our clients to optimize their loyalty program, e.g., recommendation engine for better customer engagement and retention, rules conflict detection, prediction engine for customer churn and LTV.
• Preprocess, clean, and transform data to be used for model training and evaluation.
  Experiment with different algorithms, hyperparameters, and features to optimize model performance.
• Build and train machine learning models, ensuring high accuracy and reliability.
• Deploy trained models as APIs and endpoints for real-time predictions.
• Work with software engineers to integrate machine learning models into production systems.
• Monitor and maintain deployed models, making improvements as necessary.
• Stay up-to-date with the latest advancements in machine learning and cloud computing.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Mathematics, Statistics, or a related field.
• 5+ years of software development experience, including 3+ years in developing and deploying machine learning models; hands-on experience with ML tools such as Amazon SageMaker, Posit, or TensorFlow would be a plus.
• Strong understanding of machine learning concepts and algorithms, including supervised and unsupervised learning, feature engineering, and model evaluation.
• Proficiency in SQL and noSQL databases, Python programming, and relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Familiarity with Amazon Web Services (AWS) and cloud computing concepts.
• Experience with data preprocessing, cleaning, and feature engineering.
• Good understanding of software engineering principles and best practices for deploying production-ready machine learning models.
• Strong communication and collaboration skills; able to work effectively in cross-functional teams.