Senior MLOps Engineer / Data Scientist

Project Description:

We are seeking a highly skilled Senior MLOps Engineer / Data Scientist with a strong background in the Retail industry and Order-to-Cash (O2C) domains. The ideal candidate brings extensive development experience, including a deep foundation in programming and automation. In this role, you will bridge the gap between data science and production engineering. You will design, build, and maintain end-to-end Machine Learning pipelines. You will leverage Snowflake ML and Python to deploy scalable models. You will also use Azure DevOps for robust CI/CD automation. Additionally, you will translate complex data into actionable business insights using Power BI.

Responsibilities:

• End-to-End MLOps: Design, deploy, and monitor scalable ML pipelines from data ingestion to model deployment and retraining.

• Snowflake ML Development: Utilize Snowpark, Snowflake Cortex AI, and Model Registry to build and manage in-data-warehouse machine learning solutions.

• Pipeline Automation: Build and maintain CI/CD pipelines using Azure DevOps for seamless, automated model deployment and testing.

• Domain Analytics: Apply ML models to optimize the Order-to-Cash (O2C) lifecycle, improving cash application, billing efficiency, and credit risk assessments.

• Retail Solutions: Deliver data-driven solutions for retail use cases, including demand forecasting, inventory management, and customer analytics.

• Business Intelligence: Create interactive Power BI dashboards and data models to translate complex ML outputs into clear executive insights.

Mandatory Skills Description:

• Python Expertise: Minimum of 5\+ years of hands-on, professional Python development experience writing clean, production-grade code.

• Snowflake Ecosystem: Hands-on experience with Snowflake ML tools (Snowpark, Cortex AI, or Feature Store).

• DevOps Tools: Proven experience with Azure DevOps, Git, and automated CI/CD workflows.

• BI Tools: Strong knowledge or experience with Power BI, including DAX and data modeling techniques.

• Domain Experience: Deep understanding of the Retail industry and functional knowledge of the Order-to-Cash (O2C) process.

• Education: Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.

9\+ years of Domain Experience: Retail Industry, Demand forecasting, Inventory optimization, Customer analytics, Order-to-Cash (O2C) Billing, Cash application

Nice-to-Have Skills Description:

Azure Machine Learning, Docker, Kubernetes, MLflow, Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, Snowflake SQL, ETL/ELT, Data Warehousing, Azure Data Factory, Power Query, Time Series Forecasting, Demand Forecasting, Inventory Management, Customer Analytics, Credit Risk Analytics, REST APIs, PyTest, Agile/Scrum, Statistics, Feature Engineering, Experiment Tracking.

Languages:

English: C1 Advanced