Description
The ideal candidate should have hands-on experience across the complete data science lifecycle, including data exploration, feature engineering, model development, evaluation, deployment, monitoring, and optimization.

Responsibilities

- Analyze large structured and unstructured datasets to identify patterns, trends, and actionable insights.
- Develop and implement machine learning and statistical models for business use cases.
- Perform data cleaning, preprocessing, exploratory data analysis, and feature engineering.
- Build predictive models using supervised and unsupervised learning techniques.
- Develop solutions for classification, regression, clustering, forecasting, anomaly detection, and recommendation use cases.
- Use Python and SQL for data manipulation, analysis, and model development.
- Develop and optimize ML models using libraries such as Scikit-learn, Pandas, NumPy, TensorFlow, or PyTorch.
- Design appropriate model validation and evaluation strategies using relevant performance metrics.
- Build reusable data science pipelines and production-ready ML solutions.
- Collaborate with Data Engineers, ML Engineers, Software Engineers, Product Owners, and business stakeholders.




- Work with large-scale data processing platforms and cloud environments.
- Deploy machine learning models through APIs, batch processing, or real-time inference pipelines.
- Implement MLOps practices covering model versioning, deployment, monitoring, retraining, and governance.
- Develop prototypes and proof-of-concepts for new AI/ML use cases.
- Present complex analytical findings to both technical and non-technical stakeholders.
- Ensure data quality, security, privacy, explainability, and responsible AI practices.

Qualifications

- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Artificial Intelligence, Machine Learning, Engineering, or a related discipline.
- 5+ years of relevant experience in Data Science, Machine Learning, or advanced analytics.
- Solid analytical and problem-solving capabilities.
- Excellent communication and stakeholder-management skills.
- Ability to translate business problems into appropriate data science and AI/ML solutions.
- Experience working in Agile and enterprise development environments.
- Banking, payments, financial services, or other large-scale enterprise experience is preferred.

📌 Data Scientist-3 (Pune)
🏢 Zensar Technologies
📍 Pune