Senior MLOps Engineer / Data Scientist
Skills
About the role
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
Key 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.
Required Skills & Qualifications (Mandatory)
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.
Skills
Must have
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.
9+ years of Domain Experience: Retail Industry, Demand forecasting, Inventory optimization, Customer analytics, Order-to-Cash (O2C) Billing, Cash application
Nice to have
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.
Other
Languages
English: C1 Advanced
Seniority
Senior
Remote India, India
Req. VR-124096
AI/ML
Cross Industry Solutions
20/07/2026
Req. VR-124096
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