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Remote mid-senior ML role with common big-data skills drives high applicant competition.
ML production and big-data skills transferable broadly, though AdTech domain adds moderate bias.
Mandatory 5+ years and specific ML, big-data, and AWS stack make shortlisting highly strict.
Design, build, and deploy scalable machine learning models into production systems, leveraging big data platforms and cloud services.
Develop end-to-end data science workflows including data preprocessing, feature engineering, model training, validation, and deployment using Python, SQL, Spark, and AWS tools.
Own and drive data-driven solutions independently with high accountability, focusing on optimizing query performance, storage, and pipeline efficiency.
Minimum 5 years of experience in Data Science or Applied Machine Learning.
Strong proficiency in Python, SQL, and ML libraries such as Pandas, Scikit-learn, TensorFlow, and PyTorch.
Experience with big data platforms including Hadoop and Spark, and cloud services on AWS (S3, Lambda, SageMaker, EC2).
Hands-on experience with Databricks, Airflow, and AWS EMR for automation and orchestration.
Experienced in executing end-to-end ML model deployment and optimization in production environments at scale.
Technically deep with expertise in big data processing and cloud-native ML workflows using AWS and Databricks.
Capable of independent ownership of data science initiatives with strong problem-solving aptitude in fast-paced, cross-functional settings.