Data Scientist

Experienced Senior Professional: You bring 5+ years of hands-on experience in data science, with a proven track record of designing, building, and deploying machine learning models.

Hybrid Mindset (Technical + Functional): You have a strong engineering background with deep technical rigor, but you also possess a functional mindset. You understand the business context, communicate effectively with stakeholders, and bridge the gap between technical complexity and business value.

MLOps & Engineering Native: You care deeply about clean code, continuous integration, model lifecycle management, and scalable data engineering.

Develop & Train Models: Build, optimize, and scale machine learning models to solve complex business problems using PySpark and Databricks.

**End-to-End MLOps & Productionization: **Utilize MLflow to track, log, and register models, taking full ownership of moving models from experimentation into robust production environments.

**Workflow Automation & Orchestration: **Design and manage data pipelines and model workflows using Airflow.

Database & Version Control Management: Query and interact with relational databases (MySQL) and maintain code standards, CI/CD pipelines, and version control using GitLab.

Collaborate & Drive Functional Impact: Work closely with cross-functional teams to translate business requirements into technical solutions and ensure models perform reliably in production.

Key Technical Stack Required:

Languages & Frameworks: PySpark, Python, Machine Learning models

Data & Orchestration Tools: Databricks, Airflow, MySQL

MLOps & DevOps: MLflow (Model registry & production deployment), GitLab, CI/CD