Sr. Data Science Engineer (ML)

TL;DR

Sr. Data Science Engineer (ML): Building and deploying end-to-end machine learning lifecycles and statistical models using Python and AWS with an accent on MMM and attribution frameworks. Focus on developing scalable ETL pipelines, implementing Bayesian methods, and optimizing model versioning with MLflow.

Location: Remote

Company

hirify.global is a technology firm specializing in data-driven decision-making and machine learning solutions.

What you will do

• Design, build, and deploy statistical models and ML algorithms using Python and AWS SageMaker.
• Lead independent EDA phases to validate data integrity and extract insights for business strategy.
• Implement model versioning and experiment tracking using MLflow to ensure reproducibility.
• Develop Python-based automation for data ingestion, transformation, and ETL pipelines.
• Collaborate on peer code reviews via GitHub and maintain high-quality technical documentation.
• Support the development of MMM and attribution frameworks utilizing Bayesian methods.

Requirements

• 3 to 6 years of professional experience in data science engineering.
• Expert proficiency in Python, specifically using pandas, numpy, matplotlib, seaborn, and plotly.
• Hands-on experience with AWS services: S3, SageMaker, DynamoDB, Glue, and Lambda.
• Strong knowledge of SQL (DDL/DML) and Cloud-Native PostgreSQL or Azure DB.
• Proven experience in statistical modeling using scikit-learn and Google Meridian.
• Proficiency with GitHub for version control, branching, and CI/CD implementation.

Nice to have

• Exposure to Marketing Mix Modeling (MMM) and attribution modeling.
• Experience with Bayesian MMM frameworks (e.g., Google Meridian).
• Knowledge of Docker and MLOps workflows.