Data Scientist

Talent Acquisition Executive - UK/Europe at Zensar Technologies We are seeking an experienced Data Scientist to design, develop, and deploy advanced AI/ML models leveraging client pricing datasets. The ideal candidate will have a strong background in statistical modeling, machine learning, and data engineering, with proven experience in building scalable solutions for pricing optimization and predictive analytics.

• Design and implement AI/ML models for pricing optimization, elasticity analysis, and revenue forecasting.
• Apply advanced algorithms (e.g., regression, tree-based models, deep learning) to large-scale pricing datasets.

• Perform exploratory data analysis (EDA) to identify patterns and anomalies in pricing data.
• Develop robust feature engineering pipelines for model accuracy and interpretability.

• Collaborate with engineering teams to deploy models into production environments.
• Ensure scalability, performance, and compliance with client requirements.

• Work closely with pricing analysts, business teams, and client stakeholders to translate business objectives into data-driven solutions.
• Present insights and recommendations through clear visualizations and reports.

• Strong proficiency in Python, R, and ML libraries (e.g., scikit-learn, Tensor Flow, PyTorch).
• Experience with pricing analytics, predictive modeling, and optimization techniques.
• Hands-on experience with SQL, big data platforms (Spark, Hadoop), and cloud services (AWS, Azure, GCP).
• Deep understanding of pricing strategies, elasticity modeling, and revenue management.
• Excellent communication and stakeholder management skills.

• Experience in Insurance.
• Familiarity with MLOps and CI/CD pipelines for ML models.
• Knowledge of generative AI or advanced NLP techniques for pricing insights.

Seniority level:
Mid-Senior level

Employment type:

Full-time Job function:
Information Technology Industries: IT Services and IT Consulting

We are seeking an experienced Data Scientist to design, develop, and deploy advanced AI/ML models leveraging client pricing datasets. The ideal candidate will have a strong background in statistical modeling, machine learning, and data engineering, with proven experience in building scalable solutions for pricing optimization and predictive analytics.,

Education:

Degree in Data Science, Computer Science, Statistics, or related field. Technical Expertise

• Strong proficiency in Python, R, and ML libraries (e.g., scikit-learn, Tensor Flow, PyTorch).
• Experience with pricing analytics, predictive modeling, and optimization techniques.
• Hands-on experience with SQL, big data platforms (Spark, Hadoop), and cloud services (AWS, Azure, GCP).
• Deep understanding of pricing strategies, elasticity modeling, and revenue management.
• Excellent communication and stakeholder management skills.
• Experience in Insurance.
• Familiarity with MLOps and CI/CD pipelines for ML models.
• Knowledge of generative AI or advanced NLP techniques for pricing insights.