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 recent 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 settings.
Banking, payments, financial services, or other large-scale enterprise experience is preferred.

📌 Data Scient Pune
🏢 Zensar Technologies
📍 Pune