Apptad - ML Data Scientist

We are seeking a talented ML Data Scientist to play a pivotal role in driving personalized customer experiences through cutting-edge Machine Learning (ML) solutions focused on pricing and recommendations. This remote and contract-only position offers an exciting opportunity to develop innovative solutions that optimize value and enhance consumer journeys.

Role Overview

• Monitor ML pipelines for batch and on-demand job types to improve pricing recommendations.
• Collaborate with cross-functional teams, including Marketing, Product, and Sales, to align your solutions with strategic objectives and deliver real-world impact.
• Conceptualize, design, and implement state-of-the-art ML models for dynamic pricing strategies and personalized product recommendations.

Key Responsibilities

• Develop, implement, and deploy machine learning models using user behavior and subscription data to enhance consumer value.
• Engineer and maintain large-scale consumer behavioral feature stores, ensuring scalability and performance.
• Create and maintain data pipelines and infrastructure to support efficient ML model development and deployment.
• Design, analyze, and troubleshoot controlled experiments (Causal A/B tests, Multivariate tests) to validate solutions and measure their effectiveness.
• Adopt an agile development mindset, iterating constantly to improve outputs while balancing quality and business practicality.

About You

• Bachelor's degree in Computer Science or related fields; Master’s or PhD in Machine Learning, Statistics, Data Science, or related quantitative fields preferred.
• 5 years of experience in machine learning engineering, including deep learning, recommendation systems, and data mining.
• Proficient in Python and SQL, with intermediate data engineering skills using tools and libraries such as MapReduce, Hadoop, Spark, and Big Data technologies (e.g., scikit-learn, Keras, TensorFlow, PyTorch, PySpark).
• Experience with ML techniques and frameworks such as data discretization, normalization, sampling, linear regression, decision trees, and deep neural networks.
• Experience with MLOps and solution design is a plus.

Nice to Have

• Experience in a consumer or B2C space for a SaaS product/software provider.
• Experience in developing recommendation systems and deep learning-based models.
• Excellent problem-solving skills, with the ability to navigate through ambiguous situations.

We encourage you to apply if you are ready to make a tangible difference in the lives of customers by developing innovative ML solutions that enhance their experiences. Join us and be part of a dynamic team that values flexibility and communication!