Job Descriptions

Location: Mumbai

Employment Type: Full-time

Key Responsibilities
- Develop and implement machine learning models to address business problems
- Build and maintain scalable data pipelines and reporting systems
- Design and optimize data models for structured and unstructured data
- Conduct exploratory data analysis to uncover patterns, trends, and insights
- Prepare and clean datasets for analysis and model building
- Create visualizations, dashboards, and reports to communicate insights effectively
- Write and optimize SQL queries to extract, transform, and analyze large datasets
- Collaborate with business stakeholders and cross-functional teams to understand requirements and deliver solutions
- Identify customer behavior patterns and drive business strategy through insights
- Ensure data quality, accuracy, governance, and security across workflows
- Implement CI/CD pipelines and manage ML Ops processes including deployment and monitoring
- Leverage Azure cloud services to build and manage data solutions
- Document processes, data models, dashboards,



and best practices
- Develop standardized reporting templates and visualization practices
- Present findings and insights to stakeholders with explicit storytelling

Qualifications / Experience
- Proficiency in Python and SQL for data processing and analysis
- Strong experience with SQL querying and data manipulation
- Experience with Power BI or similar visualization tools (including dashboards and reporting)
- Understanding of statistical techniques and machine learning algorithms
- Knowledge of machine learning approaches (Regression, Classification, Clustering, NLP, etc.)
- Experience with data modeling, ETL/ELT processes, and pipelines
- Hands-on experience with cloud platforms (preferably Azure)
- Familiarity with ML workflows and deployment strategies
- Experience with Docker, CI/CD tools, and version control (Git)
- Strong analytical thinking and problem-solving skills
- Excellent communication

📌 Trent Digital Team (India)
🏢 Trent
📍 India