Job Summary

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.

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: Solid 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
- 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

Location - pune,mumbai,chennai,banagalore

📌 Senior MLOps Engineer / Data Scientist (Chennai)
🏢 Luxoft
📍 Chennai