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Job Description
Structured overview of role & requirementsAbout This Role
Design, build, and deploy scalable machine learning models focused on customer value management and personalization, including model fine-tuning and optimization.
Develop new machine learning algorithms addressing emerging business challenges in customer analytics.
Prepare and curate data for advanced analytics, ensuring high-quality input features, using tools like Python, PySpark, and Kedro in a cloud environment (AWS, GCP, Azure).
Minimum Requirements
Minimum 6 years of experience in data engineering and software engineering best practices, including unit testing and data validation.
Proficiency in Python coding, distributed computing frameworks (Spark, ibis), containerization (Docker), and analytics libraries (pandas, numpy, scikit-learn).
Experience with cloud platforms (AWS, Azure, GCP), Databricks, and GitHub is required.
Degree in Computer Science, Software Engineering, or equivalent experience preferred.
Ideal Candidate Profile
Experienced in building robust data pipelines for advanced analytics in production environments.
Skilled in integrating and optimizing machine learning models for business impact in customer value management domain.
Familiar with Generative AI technologies (OpenAI GPT-4, AI Agents, prompt engineering) indicating innovation orientation and cutting-edge tech adoption.