Senior MLOps Engineer / Data Scientist

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: 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

• 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