Role & responsibilities

- Analyse business problems and identify suitable data science or machine learning approaches.
- Prepare, clean and explore structured and unstructured datasets.
- Build, test and evaluate machine learning models using established algorithms.
- Develop solutions for classification, regression, forecasting, segmentation and anomaly detection.
- Work with data engineers to build reliable data and feature pipelines.
- Deploy models or analytical solutions into cloud environments.
- Monitor model performance, data quality and model drift.
- Document assumptions, experiments, results and limitations.
- Keep up to date with developments in machine learning, GenAI and cloud AI services.
- Work with technical and business teams to explain findings and translate them into practical solutions.

Preferred candidate profile

- 34 years of practical experience in data science,



machine learning or applied analytics.
- Solid understanding of core statistics and machine learning concepts.
- Hands-on experience with Python, SQL, Pandas and Scikit-learn.
- Experience with data preparation, feature engineering, model training and evaluation.
- Understanding of common algorithms such as regression, decision trees, random forests and clustering.
- Experience working with Azure or AWS data and AI services.
- Familiarity with Databricks, Snowflake, Microsoft Fabric or similar modern data platforms.
- Experience using Git and CI/CD practices.
- Ability to explain technical results clearly to non-technical stakeholders.
- Strong willingness to learn and adopt new tools, frameworks and AI capabilities.

📌 Data Science Engineer (Ahmedabad)
🏢 Sync Origins
📍 Ahmedabad